Pre-trained Models
This page describes how to download pre-trained FireRedAsr models.
sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16 (Chinese + English, 普通话、四川话、河南话等)
This model is converted from https://huggingface.co/FireRedTeam/FireRedASR-AED-L
It supports the following 2 languages:
Chinese (普通话, 四川话、天津话、河南话等方言)
English
In the following, we describe how to download it.
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-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
tar xvf sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
rm sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
After downloading, you should find the following files:
ls -lh sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/
total 1.7G
-rw-r--r-- 1 kuangfangjun root 188 Feb 16 16:22 README.md
-rw-r--r-- 1 kuangfangjun root 425M Feb 16 16:21 decoder.int8.onnx
-rw-r--r-- 1 kuangfangjun root 1.3G Feb 16 16:21 encoder.int8.onnx
drwxr-xr-x 10 kuangfangjun root 0 Feb 16 16:26 test_wavs
-rw-r--r-- 1 kuangfangjun root 70K Feb 16 16:21 tokens.txt
ls -lh sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/
total 1.9M
-rw-r--r-- 1 kuangfangjun root 315K Feb 16 16:24 0.wav
-rw-r--r-- 1 kuangfangjun root 160K Feb 16 16:24 1.wav
-rw-r--r-- 1 kuangfangjun root 147K Feb 16 16:24 2.wav
-rw-r--r-- 1 kuangfangjun root 245K Feb 16 16:25 3-sichuan.wav
-rw-r--r-- 1 kuangfangjun root 276K Feb 16 16:24 3.wav
-rw-r--r-- 1 kuangfangjun root 245K Feb 16 16:25 4-tianjin.wav
-rw-r--r-- 1 kuangfangjun root 250K Feb 16 16:26 5-henan.wav
-rw-r--r-- 1 kuangfangjun root 276K Feb 16 16:24 8k.wav
Decode a file
Please use the following command to decode a wave file:
./build/bin/sherpa-onnx-offline \
--tokens=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/tokens.txt \
--fire-red-asr-encoder=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/encoder.int8.onnx \
--fire-red-asr-decoder=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/decoder.int8.onnx \
--num-threads=1 \
./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/0.wav
You should see the following output:
/star-fj/fangjun/open-source/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:375 ./build/bin/sherpa-onnx-offline --tokens=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/tokens.txt --fire-red-asr-encoder=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/encoder.int8.onnx --fire-red-asr-decoder=./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/decoder.int8.onnx --num-threads=1 ./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/0.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), fire_red_asr=OfflineFireRedAsrModelConfig(encoder="./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/encoder.int8.onnx", decoder="./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/decoder.int8.onnx"), tdnn=OfflineTdnnModelConfig(model=""), zipformer_ctc=OfflineZipformerCtcModelConfig(model=""), wenet_ctc=OfflineWenetCtcModelConfig(model=""), sense_voice=OfflineSenseVoiceModelConfig(model="", language="auto", use_itn=False), moonshine=OfflineMoonshineModelConfig(preprocessor="", encoder="", uncached_decoder="", cached_decoder=""), telespeech_ctc="", tokens="./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/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-fire-red-asr-large-zh_en-2025-02-16/test_wavs/0.wav
{"lang": "", "emotion": "", "event": "", "text": "昨天是 MONDAY TODAY IS礼拜二 THE DAY AFTER TOMORROW是星期三", "timestamps": [], "tokens":["昨", "天", "是", " MO", "ND", "AY", " TO", "D", "AY", " IS", "礼", "拜", "二", " THE", " DAY", " AFTER", " TO", "M", "OR", "ROW", "是", "星", "期", "三"], "words": []}
----
num threads: 1
decoding method: greedy_search
Elapsed seconds: 19.555 s
Real time factor (RTF): 19.555 / 10.053 = 1.945