Pre-trained Models

This page describes how to download pre-trained SenseVoice models.

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17 (Chinese, English, Japanese, Korean, Cantonese, 中英日韩粤语)

This model is converted from https://www.modelscope.cn/models/iic/SenseVoiceSmall using the script export-onnx.py.

It supports the following 5 languages:

• Chinese (Mandarin, 普通话)

• Cantonese (粤语, 广东话)

• English

• Japanese

• Korean

In the following, we describe how to use it.

Hint

For RKNN users, please refer to sherpa-onnx-rk3588-20-seconds-sense-voice-zh-en-ja-ko-yue-2024-07-17 (Chinese, English, Japanese, Korean, Cantonese, 中英日韩粤语).

Huggingface space

You can visit

https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition

to try this model in your browser.

Hint

You need to first select the language Chinese+English+Cantonese+Japanese+Korean and then select the model csukuangfj/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.

Android APKs

Real-time speech recognition Android APKs can be found at

https://k2-fsa.github.io/sherpa/onnx/android/apk-simulate-streaming-asr.html

Please always download the latest version.

Hint

Please search for zh_en_ko_ja_yue-sense_voice_2024_07_17_int8.apk in the above page, e.g., sherpa-onnx-1.12.11-arm64-v8a-simulated_streaming_asr-zh_en_ko_ja_yue-sense_voice_2024_07_17_int8.apk.

Hint

For Chinese users, you can also visit https://k2-fsa.github.io/sherpa/onnx/android/apk-simulate-streaming-asr-cn.html

Download

Please use the following commands to download it:

cd /path/to/sherpa-onnx

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2

tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2

After downloading, you should find the following files:

ls -lh sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17

total 1.1G
-rw-r--r-- 1 runner docker   71 Jul 18 13:06 LICENSE
-rw-r--r-- 1 runner docker  104 Jul 18 13:06 README.md
-rwxr-xr-x 1 runner docker 5.8K Jul 18 13:06 export-onnx.py
-rw-r--r-- 1 runner docker 229M Jul 18 13:06 model.int8.onnx
-rw-r--r-- 1 runner docker 895M Jul 18 13:06 model.onnx
drwxr-xr-x 2 runner docker 4.0K Jul 18 13:06 test_wavs
-rw-r--r-- 1 runner docker 309K Jul 18 13:06 tokens.txt

ls -lh sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs

total 940K
-rw-r--r-- 1 runner docker 224K Jul 18 13:06 en.wav
-rw-r--r-- 1 runner docker 226K Jul 18 13:06 ja.wav
-rw-r--r-- 1 runner docker 145K Jul 18 13:06 ko.wav
-rw-r--r-- 1 runner docker 161K Jul 18 13:06 yue.wav
-rw-r--r-- 1 runner docker 175K Jul 18 13:06 zh.wav

Hint

If you only need the int8 model file, please use:

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2024-07-17.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2024-07-17.tar.bz2

ls -lh sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2024-07-17

It prints:

total 229M
-rwxr-xr-x 1 1001 118 5.8K Jul 18  2024 export-onnx.py
-rw-r--r-- 1 1001 118   71 Jul 18  2024 LICENSE
-rw-r--r-- 1 1001 118 229M Jul 18  2024 model.int8.onnx
-rw-r--r-- 1 1001 118  104 Jul 18  2024 README.md
drwxr-xr-x 2 1001 118 4.0K Jul 18  2024 test_wavs
-rw-r--r-- 1 1001 118 309K Jul 18  2024 tokens.txt

Decode a file with model.onnx

Without inverse text normalization

To decode a file without inverse text normalization, please use:

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx \
  --num-threads=1 \
  --debug=0 \
  ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav \
  ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav

You should see the following output:

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:375 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx --num-threads=1 --debug=0 ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx", language="auto", use_itn=False), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="")
Creating recognizer ...
Started
Done!

./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav
{"text": "开饭时间早上九点至下午五点", "timestamps": [0.72, 0.96, 1.26, 1.44, 1.92, 2.10, 2.58, 2.82, 3.30, 3.90, 4.20, 4.56, 4.74], "tokens":["开", "饭", "时", "间", "早", "上", "九", "点", "至", "下", "午", "五", "点"], "words": []}
----
./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav
{"text": "the tribal chieftain called for the boy and presented him with fifty pieces of gold", "timestamps": [0.90, 1.26, 1.56, 1.80, 2.16, 2.46, 2.76, 2.94, 3.12, 3.60, 3.96, 4.50, 4.74, 5.10, 5.52, 5.88, 6.18], "tokens":["the", " tri", "bal", " chief", "tain", " called", " for", " the", " boy", " and", " presented", " him", " with", " fifty", " pieces", " of", " gold"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 2.320 s
Real time factor (RTF): 2.320 / 12.744 = 0.182

With inverse text normalization

To decode a file with inverse text normalization, please use:

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx \
  --num-threads=1 \
  --sense-voice-use-itn=1 \
  --debug=0 \
  ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav \
  ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav

You should see the following output:

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:375 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx --num-threads=1 --sense-voice-use-itn=1 --debug=0 ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx", language="auto", use_itn=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="")
Creating recognizer ...
Started
Done!

./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav
{"text": "开放时间早上9点至下午5点。", "timestamps": [0.72, 0.96, 1.26, 1.44, 1.92, 2.10, 2.58, 2.82, 3.30, 3.90, 4.20, 4.56, 4.74, 5.46], "tokens":["开", "放", "时", "间", "早", "上", "9", "点", "至", "下", "午", "5", "点", "。"], "words": []}
----
./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/en.wav
{"text": "The tribal chieftain called for the boy and presented him with 50 pieces of gold.", "timestamps": [0.90, 1.26, 1.56, 1.80, 2.16, 2.46, 2.76, 2.94, 3.12, 3.60, 3.96, 4.50, 4.74, 4.92, 5.10, 5.28, 5.52, 5.88, 6.18, 7.02], "tokens":["The", " tri", "bal", " chief", "tain", " called", " for", " the", " boy", " and", " presented", " him", " with", " ", "5", "0", " pieces", " of", " gold", "."], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.543 s
Real time factor (RTF): 1.543 / 12.744 = 0.121

Hint

When inverse text normalziation is enabled, the results also punctuations.

Specify a language

If you don’t provide a language when decoding, it uses auto.

To specify the language when decoding, please use:

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx \
  --num-threads=1 \
  --sense-voice-language=zh \
  --debug=0 \
  ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav

You should see the following output:

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:375 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx --num-threads=1 --sense-voice-language=zh --debug=0 ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.onnx", language="zh", use_itn=False), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="")
Creating recognizer ...
Started
Done!

./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/test_wavs/zh.wav
{"text": "开饭时间早上九点至下午五点", "timestamps": [0.72, 0.96, 1.26, 1.44, 1.92, 2.10, 2.58, 2.82, 3.30, 3.90, 4.20, 4.56, 4.74], "tokens":["开", "饭", "时", "间", "早", "上", "九", "点", "至", "下", "午", "五", "点"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.625 s
Real time factor (RTF): 0.625 / 5.592 = 0.112

Hint

Valid values for --sense-voice-language are auto, zh, en, ko, ja, and yue. where zh is for Chinese, en for English, ko for Korean, ja for Japanese, and yue for Cantonese.

Speech recognition from a microphone

./build/bin/sherpa-onnx-microphone-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx

Speech recognition from a microphone with VAD

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx

./build/bin/sherpa-onnx-vad-microphone-offline-asr \
  --silero-vad-model=./silero_vad.onnx \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09 (Chinese, English, Japanese, Korean, Cantonese, 中英日韩粤语)

This model is converted from

https://huggingface.co/ASLP-lab/WSYue-ASR/tree/main/sensevoice_small_yue

It is fine-tuned on sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17 (Chinese, English, Japanese, Korean, Cantonese, 中英日韩粤语) with 21.8k hours of Cantonese data.

It supports the following 5 languages:

• Chinese (Mandarin, 普通话)

• Cantonese (粤语, 广东话)

• English

• Japanese

• Korean

Hint

If you want a Cantonese ASR model, please choose this model or sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10 (Cantonese, 粤语)

Hint

For RKNN users, please refer to sherpa-onnx-rk3588-20-seconds-sense-voice-zh-en-ja-ko-yue-2025-09-09 (Chinese, English, Japanese, Korean, Cantonese, 中英日韩粤语).

In the following, we describe how to use it.

Huggingface space

You can visit

https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition

to try this model in your browser.

Hint

You need to first select the language Chinese+English+Cantonese+Japanese+Korean and then select the model csukuangfj/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09.

Android APKs

Real-time speech recognition Android APKs can be found at

https://k2-fsa.github.io/sherpa/onnx/android/apk-simulate-streaming-asr.html

Please always download the latest version.

Hint

Please search for zh_en_ko_ja_yue-sense_voice_2025_09_09_int8.apk in the above page, e.g., sherpa-onnx-1.12.11-arm64-v8a-simulated_streaming_asr-zh_en_ko_ja_yue-sense_voice_2025_09_09_int8.apk.

Hint

For Chinese users, you can also visit https://k2-fsa.github.io/sherpa/onnx/android/apk-simulate-streaming-asr-cn.html

Download

Please use the following commands to download it:

cd /path/to/sherpa-onnx

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09.tar.bz2

After downloading, you should find the following files:

ls -lh sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09

total 492952
-rw-r--r--   1 fangjun  staff   131B Sep  9 21:12 README.md
-rw-r--r--   1 fangjun  staff   226M Sep  9 21:12 model.int8.onnx
drwxr-xr-x  25 fangjun  staff   800B Sep  9 21:12 test_wavs
-rw-r--r--   1 fangjun  staff   308K Sep  9 21:12 tokens.txt

ls  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/

en.wav     ko.wav     yue-1.wav  yue-11.wav yue-13.wav yue-15.wav yue-17.wav yue-3.wav  yue-5.wav  yue-7.wav  yue-9.wav  zh.wav
ja.wav     yue-0.wav  yue-10.wav yue-12.wav yue-14.wav yue-16.wav yue-2.wav  yue-4.wav  yue-6.wav  yue-8.wav  yue.wav

In the following, we show how to decode the files sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-*.wav.

yue-0.wav

Wave filename	Content	Ground truth
yue-0.wav		两只小企鹅都有嘢食

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-0.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-0.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-0.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "两只小企鹅都有嘢食", "timestamps": [0.36, 0.60, 0.84, 1.08, 1.32, 1.74, 1.98, 2.16, 2.40], "tokens":["两", "只", "小", "企", "鹅", "都", "有", "嘢", "食"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.284 s
Real time factor (RTF): 0.284 / 3.072 = 0.092

yue-1.wav

Wave filename	Content	Ground truth
yue-1.wav		叫做诶诶直入式你个脑部里边咧记得呢一个嘅以前香港有一个广告好出名嘅佢乜嘢都冇噶净系影住喺弥敦道佢哋间铺头嘅啫但系就不停有人嗌啦平平吧平吧

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-1.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-1.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-1.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "叫做诶诶直入式你个脑部里边呢记得呢一个嘅以前香港有一个广告好出名嘅佢乜嘢都冇噶净系影住喺弥敦度佢哋间铺头嘅啫但系就不停有人嗌啦平平吧平吧", "timestamps": [0.06, 0.18, 0.36, 0.72, 1.08, 1.38, 1.56, 1.86, 1.98, 2.16, 2.52, 2.76, 2.88, 3.00, 3.24, 3.36, 3.60, 3.72, 3.84, 3.96, 4.20, 4.32, 4.44, 4.62, 4.74, 4.86, 4.92, 5.04, 5.16, 5.34, 5.46, 5.58, 5.88, 6.30, 6.60, 6.78, 6.90, 7.02, 7.20, 7.50, 7.68, 7.80, 7.98, 8.16, 8.28, 8.46, 8.64, 8.88, 8.94, 9.18, 9.30, 9.48, 9.60, 9.78, 10.02, 10.14, 10.26, 10.50, 10.62, 10.80, 10.92, 11.04, 11.22, 12.00, 12.72, 13.02, 13.92, 14.16], "tokens":["叫", "做", "诶", "诶", "直", "入", "式", "你", "个", "脑", "部", "里", "边", "呢", "记", "得", "呢", "一", "个", "嘅", "以", "前", "香", "港", "有", "一", "个", "广", "告", "好", "出", "名", "嘅", "佢", "乜", "嘢", "都", "冇", "噶", "净", "系", "影", "住", "喺", "弥", "敦", "度", "佢", "哋", "间", "铺", "头", "嘅", "啫", "但", "系", "就", "不", "停", "有", "人", "嗌", "啦", "平", "平", "吧", "平", "吧"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.423 s
Real time factor (RTF): 1.423 / 15.104 = 0.094

yue-2.wav

Wave filename	Content	Ground truth
yue-2.wav		忽然从光线死角嘅阴影度窜出一只大猫

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-2.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-2.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-2.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "忽然从光线死角嘅阴影度窜出一只大猫", "timestamps": [0.36, 0.54, 0.96, 1.26, 1.50, 1.80, 2.04, 2.22, 2.40, 2.52, 2.76, 3.12, 3.30, 3.48, 3.60, 3.78, 3.90], "tokens":["忽", "然", "从", "光", "线", "死", "角", "嘅", "阴", "影", "度", "窜", "出", "一", "只", "大", "猫"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.428 s
Real time factor (RTF): 0.428 / 4.608 = 0.093

yue-3.wav

Wave filename	Content	Ground truth
yue-3.wav		今日我带大家去见识一位九零后嘅靓仔咧

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-3.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-3.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-3.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "今日我带大家去见识一位九零后嘅靓仔咧", "timestamps": [0.24, 0.36, 0.60, 0.72, 1.02, 1.14, 1.44, 1.74, 1.92, 2.10, 2.22, 2.52, 2.76, 2.94, 3.18, 3.30, 3.48, 3.78], "tokens":["今", "日", "我", "带", "大", "家", "去", "见", "识", "一", "位", "九", "零", "后", "嘅", "靓", "仔", "咧"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.438 s
Real time factor (RTF): 0.438 / 4.352 = 0.101

yue-4.wav

Wave filename	Content	Ground truth
yue-4.wav		香港嘅消费市场从此不一样

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-4.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-4.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-4.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "香港嘅消费市场从此不一样", "timestamps": [0.36, 0.54, 0.72, 0.90, 1.08, 1.38, 1.56, 1.92, 2.10, 2.40, 2.58, 2.76], "tokens":["香", "港", "嘅", "消", "费", "市", "场", "从", "此", "不", "一", "样"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.303 s
Real time factor (RTF): 0.303 / 3.200 = 0.095

yue-5.wav

Wave filename	Content	Ground truth
yue-5.wav		景天谂唔到呢个守门嘅弟子竟然咁无礼霎时间面色都变埋

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-5.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-5.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-5.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "景天谂唔到呢个守门嘅弟子竟然咁无礼霎时间面色都变埋", "timestamps": [0.42, 0.60, 0.96, 1.14, 1.20, 1.38, 1.50, 1.62, 1.86, 2.04, 2.22, 2.34, 3.06, 3.24, 3.42, 3.84, 4.08, 4.80, 5.16, 5.34, 5.58, 5.82, 6.06, 6.24, 6.42], "tokens":["景", "天", "谂", "唔", "到", "呢", "个", "守", "门", "嘅", "弟", "子", "竟", "然", "咁", "无", "礼", "霎", "时", "间", "面", "色", "都", "变", "埋"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.660 s
Real time factor (RTF): 0.660 / 7.168 = 0.092

yue-6.wav

Wave filename	Content	Ground truth
yue-6.wav		六个星期嘅课程包括六堂课同两个测验你唔掌握到基本嘅十九个声母五十六个韵母同九个声调我哋仲针对咗广东话学习者会遇到嘅大樽颈啊以国语为母语人士最难掌握嘅五大韵母教课书唔会教你嘅七种变音同十种变调说话生硬唔自然嘅根本性问题提供全新嘅学习方向等你突破难关

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-6.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-6.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-6.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "六个星期嘅课程包括六堂课同两个测验你只掌握到基本嘅十九个声母五十六个韵母同九个声调我哋仲针对咗广东话学习者会遇到嘅大樽颈啊以国语为母语人士最难掌握嘅五大韵母教课书唔会教你嘅七种变音同十种变调说话生硬唔自然嘅根本性问题提供全新嘅学习方向等你突破难关", "timestamps": [0.36, 0.66, 0.84, 1.08, 1.26, 1.44, 1.68, 2.16, 2.34, 2.58, 2.76, 2.94, 3.36, 3.60, 3.78, 4.02, 4.26, 4.86, 5.16, 5.40, 5.52, 5.70, 5.94, 6.06, 6.30, 6.54, 6.78, 6.96, 7.08, 7.32, 7.68, 7.80, 7.98, 8.10, 8.28, 8.52, 8.88, 9.12, 9.36, 9.54, 9.72, 10.14, 10.26, 10.44, 10.56, 10.74, 10.92, 11.22, 11.34, 11.52, 11.70, 11.82, 12.00, 12.42, 12.66, 12.84, 13.02, 13.44, 13.74, 13.98, 14.22, 14.52, 14.82, 15.00, 15.24, 15.42, 15.60, 15.84, 15.90, 16.32, 16.62, 16.86, 17.10, 17.28, 17.64, 17.82, 18.06, 18.30, 18.78, 19.02, 19.20, 19.50, 19.62, 19.80, 19.98, 20.16, 20.34, 20.58, 20.82, 21.00, 21.30, 21.54, 21.78, 22.02, 22.20, 22.98, 23.28, 23.52, 23.70, 24.18, 24.36, 24.60, 24.78, 25.14, 25.38, 25.68, 25.92, 26.04, 26.52, 26.70, 27.00, 27.18, 27.42, 27.60, 27.72, 27.90, 28.08, 28.50, 28.74, 29.28, 29.46, 29.76, 29.94], "tokens":["六", "个", "星", "期", "嘅", "课", "程", "包", "括", "六", "堂", "课", "同", "两", "个", "测", "验", "你", "只", "掌", "握", "到", "基", "本", "嘅", "十", "九", "个", "声", "母", "五", "十", "六", "个", "韵", "母", "同", "九", "个", "声", "调", "我", "哋", "仲", "针", "对", "咗", "广", "东", "话", "学", "习", "者", "会", "遇", "到", "嘅", "大", "樽", "颈", "啊", "以", "国", "语", "为", "母", "语", "人", "士", "最", "难", "掌", "握", "嘅", "五", "大", "韵", "母", "教", "课", "书", "唔", "会", "教", "你", "嘅", "七", "种", "变", "音", "同", "十", "种", "变", "调", "说", "话", "生", "硬", "唔", "自", "然", "嘅", "根", "本", "性", "问", "题", "提", "供", "全", "新", "嘅", "学", "习", "方", "向", "等", "你", "突", "破", "难", "关"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 3.411 s
Real time factor (RTF): 3.411 / 30.592 = 0.111

yue-7.wav

Wave filename	Content	Ground truth
yue-7.wav		同意嘅累积唔系阴同阳嘅累积可以讲三既融合咗一同意融合咗阴同阳

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-7.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-7.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-7.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "同二嘅累积唔系阴同阳嘅累积可以讲三既融合咗一同二融合咗阴同阳", "timestamps": [0.48, 0.84, 1.20, 1.38, 1.56, 2.52, 2.70, 3.00, 3.42, 3.66, 3.96, 4.20, 4.38, 5.40, 5.76, 6.00, 6.78, 7.86, 8.28, 8.46, 8.70, 9.24, 9.72, 10.08, 11.28, 11.46, 11.70, 12.12, 12.54, 12.78], "tokens":["同", "二", "嘅", "累", "积", "唔", "系", "阴", "同", "阳", "嘅", "累", "积", "可", "以", "讲", "三", "既", "融", "合", "咗", "一", "同", "二", "融", "合", "咗", "阴", "同", "阳"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.382 s
Real time factor (RTF): 1.382 / 13.900 = 0.099

yue-8.wav

Wave filename	Content	Ground truth
yue-8.wav		而较早前已经复航嘅氹仔北安码头星期五开始增设夜间航班不过两个码头暂时都冇凌晨班次有旅客希望尽快恢复可以留喺澳门长啲时间

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-8.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-8.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-8.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "而较早前已经复航嘅氹仔北安码头星期五开始增设夜间航班不过两个码头暂时都冇凌晨班次有旅客希望尽快恢复可以留喺澳门长啲时间", "timestamps": [0.30, 0.54, 0.72, 0.90, 1.14, 1.26, 1.50, 1.68, 1.86, 2.04, 2.28, 2.58, 2.70, 3.00, 3.12, 3.42, 3.60, 3.78, 4.02, 4.14, 4.44, 4.62, 4.92, 5.04, 5.28, 5.40, 6.12, 6.36, 6.60, 6.78, 6.96, 7.14, 7.44, 7.62, 7.80, 7.98, 8.16, 8.34, 8.58, 8.76, 9.54, 9.72, 9.90, 10.14, 10.26, 10.50, 10.62, 10.92, 11.10, 11.58, 11.70, 11.94, 12.06, 12.30, 12.48, 12.78, 12.96, 13.20, 13.44], "tokens":["而", "较", "早", "前", "已", "经", "复", "航", "嘅", "氹", "仔", "北", "安", "码", "头", "星", "期", "五", "开", "始", "增", "设", "夜", "间", "航", "班", "不", "过", "两", "个", "码", "头", "暂", "时", "都", "冇", "凌", "晨", "班", "次", "有", "旅", "客", "希", "望", "尽", "快", "恢", "复", "可", "以", "留", "喺", "澳", "门", "长", "啲", "时", "间"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.406 s
Real time factor (RTF): 1.406 / 14.080 = 0.100

yue-9.wav

Wave filename	Content	Ground truth
yue-9.wav		刘备仲马鞭一指蜀兵一齐掩杀过去打到吴兵大败唉刘备八路兵马以雷霆万钧之势啊杀到吴兵啊尸横遍野血流成河

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-9.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-9.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-9.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "刘备仲马鞭得子蜀兵一齐掩杀过去打到吴兵大败嘿刘备八路兵马以雷霆万军之势啊杀到吴兵啊尸横遍野血流成河", "timestamps": [0.30, 0.54, 0.72, 0.90, 1.14, 1.32, 1.44, 2.22, 2.58, 2.88, 3.06, 3.42, 3.60, 3.90, 3.96, 4.32, 4.50, 4.68, 4.92, 5.28, 5.46, 6.06, 6.60, 6.84, 7.26, 7.56, 7.74, 7.98, 8.58, 8.88, 9.12, 9.36, 9.60, 9.84, 10.08, 10.26, 10.38, 10.56, 10.80, 10.98, 11.22, 11.58, 12.12, 12.36, 12.66, 12.90, 13.14, 13.32, 13.50], "tokens":["刘", "备", "仲", "马", "鞭", "得", "子", "蜀", "兵", "一", "齐", "掩", "杀", "过", "去", "打", "到", "吴", "兵", "大", "败", "嘿", "刘", "备", "八", "路", "兵", "马", "以", "雷", "霆", "万", "军", "之", "势", "啊", "杀", "到", "吴", "兵", "啊", "尸", "横", "遍", "野", "血", "流", "成", "河"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.438 s
Real time factor (RTF): 1.438 / 14.336 = 0.100

yue-10.wav

Wave filename	Content	Ground truth
yue-10.wav		原来王力宏咧系佢家中里面咧成就最低个吓哇

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-10.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-10.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-10.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "原来王力宏呢系佢家中里边咧成就最低个吓哇", "timestamps": [0.42, 0.54, 0.90, 1.14, 1.44, 1.62, 1.80, 1.92, 2.16, 2.34, 2.58, 2.70, 2.82, 3.06, 3.24, 3.54, 3.78, 4.26, 4.92, 5.76], "tokens":["原", "来", "王", "力", "宏", "呢", "系", "佢", "家", "中", "里", "边", "咧", "成", "就", "最", "低", "个", "吓", "哇"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.611 s
Real time factor (RTF): 0.611 / 6.656 = 0.092

yue-11.wav

Wave filename	Content	Ground truth
yue-11.wav		无论你提出任何嘅要求

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-11.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-11.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-11.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "无论你提出任何嘅要求", "timestamps": [0.48, 0.60, 0.78, 1.02, 1.14, 1.32, 1.50, 1.68, 1.86, 2.10], "tokens":["无", "论", "你", "提", "出", "任", "何", "嘅", "要", "求"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.293 s
Real time factor (RTF): 0.293 / 2.688 = 0.109

yue-12.wav

Wave filename	Content	Ground truth
yue-12.wav		咁咁多样材料咁我哋首先第一步处理咗一件

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-12.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-12.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-12.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "咁咁多样材料咁我哋首先第一步处理咗一件", "timestamps": [0.30, 0.72, 0.90, 1.14, 1.38, 1.56, 1.92, 2.10, 2.22, 2.34, 2.58, 2.88, 3.00, 3.18, 3.60, 3.84, 4.02, 4.14, 4.26], "tokens":["咁", "咁", "多", "样", "材", "料", "咁", "我", "哋", "首", "先", "第", "一", "步", "处", "理", "咗", "一", "件"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.435 s
Real time factor (RTF): 0.435 / 4.864 = 0.089

yue-13.wav

Wave filename	Content	Ground truth
yue-13.wav		啲点样对于佢哋嘅服务态度啊不透过呢一年左右嘅时间啦其实大家都静一静啦咁你就会见到香港嘅经济其实

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-13.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-13.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-13.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "啲点样对于佢哋嘅服务态度啊希透过呢一年左右嘅时间啦其实大家都静一静啦咁你就会见到香港嘅经济其实", "timestamps": [0.00, 0.24, 0.48, 0.72, 0.84, 1.08, 1.20, 1.68, 2.16, 2.34, 2.58, 2.76, 2.94, 3.24, 3.54, 3.72, 4.02, 4.32, 4.50, 4.80, 4.98, 5.16, 5.34, 5.52, 5.70, 6.06, 6.24, 6.48, 6.60, 6.78, 7.02, 7.20, 7.38, 7.56, 7.92, 8.16, 8.34, 8.52, 8.70, 8.82, 9.00, 9.18, 9.36, 9.48, 9.66, 9.96, 10.14], "tokens":["啲", "点", "样", "对", "于", "佢", "哋", "嘅", "服", "务", "态", "度", "啊", "希", "透", "过", "呢", "一", "年", "左", "右", "嘅", "时", "间", "啦", "其", "实", "大", "家", "都", "静", "一", "静", "啦", "咁", "你", "就", "会", "见", "到", "香", "港", "嘅", "经", "济", "其", "实"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.362 s
Real time factor (RTF): 1.362 / 10.624 = 0.128

yue-14.wav

Wave filename	Content	Ground truth
yue-14.wav		就即刻会同贵正两位八代长老带埋五名七代弟子前啲灵蛇岛想话生擒谢信抢咗屠龙宝刀翻嚟献俾帮主嘅

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-14.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-14.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-14.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "就即刻会同贵正两位八代长老带埋五名七代弟子前啲灵蛇岛想话生擒谢信抢咗屠龙宝都翻嚟献俾帮主嘅", "timestamps": [0.18, 0.36, 0.48, 0.72, 0.84, 1.20, 1.44, 1.74, 1.92, 2.10, 2.28, 2.52, 2.76, 3.60, 3.84, 4.14, 4.32, 4.56, 4.80, 5.04, 5.22, 5.88, 6.12, 6.24, 6.42, 6.78, 7.68, 7.92, 8.16, 8.52, 8.88, 9.18, 10.02, 10.26, 10.38, 10.62, 10.86, 11.10, 11.22, 11.40, 11.64, 11.88, 12.18, 12.30, 12.66], "tokens":["就", "即", "刻", "会", "同", "贵", "正", "两", "位", "八", "代", "长", "老", "带", "埋", "五", "名", "七", "代", "弟", "子", "前", "啲", "灵", "蛇", "岛", "想", "话", "生", "擒", "谢", "信", "抢", "咗", "屠", "龙", "宝", "都", "翻", "嚟", "献", "俾", "帮", "主", "嘅"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.293 s
Real time factor (RTF): 1.293 / 13.056 = 0.099

yue-15.wav

Wave filename	Content	Ground truth
yue-15.wav		我知道我的观众大部分都是对广东话有兴趣想学广东话的人

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-15.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-15.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-15.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "我知道我嘅观众大部分都系对广东话有兴趣想学广东话嘅人", "timestamps": [0.42, 0.54, 0.66, 0.84, 1.02, 1.20, 1.38, 1.98, 2.22, 2.40, 2.64, 2.76, 2.88, 3.12, 3.24, 3.42, 3.60, 3.78, 4.02, 4.62, 4.92, 5.16, 5.34, 5.52, 5.70, 5.94], "tokens":["我", "知", "道", "我", "嘅", "观", "众", "大", "部", "分", "都", "系", "对", "广", "东", "话", "有", "兴", "趣", "想", "学", "广", "东", "话", "嘅", "人"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.582 s
Real time factor (RTF): 0.582 / 6.400 = 0.091

yue-16.wav

Wave filename	Content	Ground truth
yue-16.wav		诶原来啊我哋中国人呢讲究物极必反

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-16.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-16.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-16.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "原来啊我哋中国人呢讲究密极必反", "timestamps": [1.92, 2.04, 2.22, 2.64, 2.76, 2.94, 3.12, 3.36, 3.48, 3.72, 3.84, 4.02, 4.20, 4.44, 4.62], "tokens":["原", "来", "啊", "我", "哋", "中", "国", "人", "呢", "讲", "究", "密", "极", "必", "反"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 0.600 s
Real time factor (RTF): 0.600 / 5.700 = 0.105

yue-17.wav

Wave filename	Content	Ground truth
yue-17.wav		如果东边道建成咁丹东呢就会成为最近嘅出海港同埋经过哈大线出海相比绥分河则会减少运渠三百五十六公里

./build/bin/sherpa-onnx-offline \
  --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt \
  --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx \
  --num-threads=1 \
  sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-17.wav

/Users/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:372 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt --sense-voice-model=./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx --num-threads=1 sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-17.wav 

OfflineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80, low_freq=20, high_freq=-400, dither=0, normalize_samples=True, snip_edges=False), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename="", decoder_filename="", joiner_filename=""), paraformer=OfflineParaformerModelConfig(model=""), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=""), whisper=OfflineWhisperModelConfig(encoder="", decoder="", language="", task="transcribe", tail_paddings=-1), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="", decoder=""), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/model.int8.onnx", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), dolphin=OfflineDolphinModelConfig(model=""), canary=OfflineCanaryModelConfig(encoder="", decoder="", src_lang="", tgt_lang="", use_pnc=True), telespeech_ctc="", tokens="./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/tokens.txt", num_threads=1, debug=False, provider="cpu", model_type="", modeling_unit="cjkchar", bpe_vocab=""), lm_config=OfflineLMConfig(model="", scale=0.5, lodr_scale=0.01, lodr_fst="", lodr_backoff_id=-1), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph="", max_active=3000), decoding_method="greedy_search", max_active_paths=4, hotwords_file="", hotwords_score=1.5, blank_penalty=0, rule_fsts="", rule_fars="", hr=HomophoneReplacerConfig(dict_dir="", lexicon="", rule_fsts=""))
Creating recognizer ...
Started
Done!

sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09/test_wavs/yue-17.wav
{"lang": "<|yue|>", "emotion": "<|NEUTRAL|>", "event": "<|Speech|>", "text": "如果东边道建成咁丹东呢就会成为最近嘅出海港同埋经过哈大线出海相比绥分河将会减少运渠三百五十六公里", "timestamps": [0.48, 0.60, 0.84, 0.96, 1.20, 1.50, 1.74, 2.58, 3.00, 3.18, 3.36, 3.78, 4.02, 4.20, 4.32, 4.56, 4.74, 4.92, 5.04, 5.22, 5.46, 6.36, 6.54, 6.78, 6.90, 7.08, 7.26, 7.50, 7.80, 7.92, 8.16, 8.34, 9.24, 9.54, 9.84, 10.26, 10.50, 10.74, 10.86, 11.22, 11.40, 11.82, 12.12, 12.30, 12.48, 12.60, 12.84, 13.02], "tokens":["如", "果", "东", "边", "道", "建", "成", "咁", "丹", "东", "呢", "就", "会", "成", "为", "最", "近", "嘅", "出", "海", "港", "同", "埋", "经", "过", "哈", "大", "线", "出", "海", "相", "比", "绥", "分", "河", "将", "会", "减", "少", "运", "渠", "三", "百", "五", "十", "六", "公", "里"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 1.335 s
Real time factor (RTF): 1.335 / 13.800 = 0.097