NeMo
This section lists models from NeMo.
sherpa-nemo-ctc-en-citrinet-512 (English)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-en-citrinet-512
cd sherpa-nemo-ctc-en-citrinet-512
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 kuangfangjun root 142M Mar 9 21:23 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-zh-citrinet-512 (Chinese)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-zh-citrinet-512
cd sherpa-nemo-ctc-zh-citrinet-512
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=true \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 kuangfangjun root 153M Mar 10 15:07 model.pt
Hint
Since the vocabulary size of this model is very large, i.e, 5207, we use
--modified=true to use a
modified CTC topology
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-zh-citrinet-1024-gamma-0-25 (Chinese)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-zh-citrinet-1024-gamma-0-25
cd sherpa-nemo-ctc-zh-citrinet-1024-gamma-0-25
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=true \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 kuangfangjun root 557M Mar 10 16:29 model.pt
Hint
Since the vocabulary size of this model is very large, i.e, 5207, we use
--modified=true to use a
modified CTC topology
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-de-citrinet-1024 (German)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-de-citrinet-1024
cd sherpa-nemo-ctc-de-citrinet-1024
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 kuangfangjun root 541M Mar 10 16:55 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-en-conformer-small (English)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-en-conformer-small
cd sherpa-nemo-ctc-en-conformer-small
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 fangjun staff 82M Mar 10 19:55 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-en-conformer-medium (English)
This model is converted from
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-en-conformer-medium
cd sherpa-nemo-ctc-en-conformer-medium
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 fangjun staff 152M Mar 10 20:26 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-en-conformer-large (English)
This model is converted from
Hint
The vocabulary size is 129
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-en-conformer-large
cd sherpa-nemo-ctc-en-conformer-large
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 fangjun staff 508M Mar 10 20:44 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
sherpa-nemo-ctc-de-conformer-large (German)
This model is converted from
Hint
The vocabulary size is 129
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-nemo-ctc-de-conformer-large
cd sherpa-nemo-ctc-de-conformer-large
git lfs pull --include "model.pt"
sherpa-offline \
--nn-model=./model.pt \
--tokens=./tokens.txt \
--use-gpu=false \
--modified=false \
--nemo-normalize=per_feature \
./test_wavs/0.wav \
./test_wavs/1.wav \
./test_wavs/2.wav
ls -lh model.pt
-rw-r--r-- 1 fangjun staff 508M Mar 10 21:34 model.pt
Caution
It is of paramount importance to specify --nemo-normalize=per_feature.
How to convert NeMo models to sherpa
This section describes how to export NeMo pre-trained CTC models to sherpa.
You can find a list of pre-trained models from NeMo by visiting:
Let us take stt_en_conformer_ctc_small as an example.
You can use the following code to obtain model.pt and tokens.txt:
import nemo.collections.asr as nemo_asr
m = nemo_asr.models.EncDecCTCModelBPE.from_pretrained('stt_en_conformer_ctc_small')
m.export("model.pt")
with open('tokens.txt', 'w', encoding='utf-8') as f:
f.write("<blk> 0\n")
for i, s in enumerate(m.decoder.vocabulary):
f.write(f"{s} {i+1}\n")
One thing to note is that the blank token has the largest token ID in NeMo.
However, it is always 0 in sherpa. During network computation, we shift
the last column of the log_prob tensor to the first column so that
it matches the convention about using 0 for the blank in sherpa.
You can find the exported model.pt and tokens.txt by visiting