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134 lines
3.6 KiB
134 lines
3.6 KiB
# Aishell - Deepspeech2 Streaming
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> We recommend using U2/U2++ model instead of DS2, please see [here](../../u2pp_ol/wenetspeech/).
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A C++ deployment example for using the deepspeech2 model to recognize `wav` and compute `CER`. We using AISHELL-1 as test data.
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## Source path.sh
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```bash
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. path.sh
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```
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SpeechX bins is under `echo $SPEECHX_BUILD`, more info please see `path.sh`.
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## Recognize with linear feature
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```bash
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bash run.sh
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```
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`run.sh` has multi stage, for details please see `run.sh`:
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1. donwload dataset, model and lm
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2. convert cmvn format and compute feature
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3. decode w/o lm by feature
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4. decode w/ ngram lm by feature
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5. decode w/ TLG graph by feature
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6. recognize w/ TLG graph by wav input
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### Recognize with `.scp` file for wav
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This sciprt using `recognizer_main` to recognize wav file.
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The input is `scp` file which look like this:
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```text
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# head data/split1/1/aishell_test.scp
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BAC009S0764W0121 /workspace/PaddleSpeech/speechx/examples/u2pp_ol/wenetspeech/data/test/S0764/BAC009S0764W0121.wav
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BAC009S0764W0122 /workspace/PaddleSpeech/speechx/examples/u2pp_ol/wenetspeech/data/test/S0764/BAC009S0764W0122.wav
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...
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BAC009S0764W0125 /workspace/PaddleSpeech/speechx/examples/u2pp_ol/wenetspeech/data/test/S0764/BAC009S0764W0125.wav
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```
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If you want to recognize one wav, you can make `scp` file like this:
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```text
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key path/to/wav/file
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```
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Then specify `--wav_rspecifier=` param for `recognizer_main` bin. For other flags meaning, please see `help`:
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```bash
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recognizer_main --help
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```
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For the exmaple to using `recognizer_main` please see `run.sh`.
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### CTC Prefix Beam Search w/o LM
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```
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Overall -> 16.14 % N=104612 C=88190 S=16110 D=312 I=465
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Mandarin -> 16.14 % N=104612 C=88190 S=16110 D=312 I=465
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Other -> 0.00 % N=0 C=0 S=0 D=0 I=0
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```
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### CTC Prefix Beam Search w/ LM
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LM: zh_giga.no_cna_cmn.prune01244.klm
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```
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Overall -> 7.86 % N=104768 C=96865 S=7573 D=330 I=327
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Mandarin -> 7.86 % N=104768 C=96865 S=7573 D=330 I=327
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Other -> 0.00 % N=0 C=0 S=0 D=0 I=0
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```
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### CTC TLG WFST
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LM: [aishell train](http://paddlespeech.bj.bcebos.com/speechx/examples/ds2_ol/aishell/aishell_graph.zip)
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--acoustic_scale=1.2
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```
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Overall -> 11.14 % N=103017 C=93363 S=9583 D=71 I=1819
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Mandarin -> 11.14 % N=103017 C=93363 S=9583 D=71 I=1818
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Other -> 0.00 % N=0 C=0 S=0 D=0 I=1
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```
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LM: [wenetspeech](http://paddlespeech.bj.bcebos.com/speechx/examples/ds2_ol/aishell/wenetspeech_graph.zip)
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--acoustic_scale=1.5
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```
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Overall -> 10.93 % N=104765 C=93410 S=9780 D=1575 I=95
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Mandarin -> 10.93 % N=104762 C=93410 S=9779 D=1573 I=95
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Other -> 100.00 % N=3 C=0 S=1 D=2 I=0
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```
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## Recognize with fbank feature
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This script is same to `run.sh`, but using fbank feature.
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```bash
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bash run_fbank.sh
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```
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### CTC Prefix Beam Search w/o LM
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```
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Overall -> 10.44 % N=104765 C=94194 S=10174 D=397 I=369
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Mandarin -> 10.44 % N=104762 C=94194 S=10171 D=397 I=369
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Other -> 100.00 % N=3 C=0 S=3 D=0 I=0
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```
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### CTC Prefix Beam Search w/ LM
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LM: zh_giga.no_cna_cmn.prune01244.klm
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```
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Overall -> 5.82 % N=104765 C=99386 S=4944 D=435 I=720
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Mandarin -> 5.82 % N=104762 C=99386 S=4941 D=435 I=720
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English -> 0.00 % N=0 C=0 S=0 D=0 I=0
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```
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### CTC TLG WFST
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LM: [aishell train](https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_graph2.zip)
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```
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Overall -> 9.58 % N=104765 C=94817 S=4326 D=5622 I=84
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Mandarin -> 9.57 % N=104762 C=94817 S=4325 D=5620 I=84
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Other -> 100.00 % N=3 C=0 S=1 D=2 I=0
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```
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## Build TLG WFST graph
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The script is for building TLG wfst graph, depending on `srilm`, please make sure it is installed.
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For more information please see the script below.
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```bash
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bash ./local/run_build_tlg.sh
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```
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