@@ -24,9 +24,9 @@ The basic process of ASR is shown in the figure below:
The main characteristics of PP-ASR are shown below:
- Provides pre-trained models on Chinese/English open source datasets: aishell(Chinese), wenetspeech(Chinese) and librispeech(English). The models includes deepspeech2 and conformer/transformer.
- Provides pre-trained models on Chinese/English open source datasets: aishell(Chinese), wenetspeech(Chinese) and librispeech(English). The models include deepspeech2 and conformer/transformer.
- Support model training on Chinese/English datasets.
- Support model inference using the command line. You can use to use `paddlespeech asr --model xxx --input xxx.wav` to use pre-trained model to do model inference.
- Support model inference using the command line. You can use to use `paddlespeech asr --model xxx --input xxx.wav` to use the pre-trained model to do model inference.
- Support deployment of streaming ASR server. Besides ASR function, the server supports timestamp function.
- Support customized auto speech recognition and deployment.
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@@ -43,21 +43,21 @@ For more information about model design, you can refer to the aistudio tutorial:
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## 3.2 Training
The reference script for model training is stored in [examples](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples) and stored according to "examples/dataset/model". The dataset mainly supports aishell and librispeech. The model supports deepspeech2 and u2(conformer/transformer).
The referenced script for model training is stored in [examples](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples) and stored according to "examples/dataset/model". The dataset mainly supports aishell and librispeech. The model supports deepspeech2 and u2(conformer/transformer).
The specific steps of executing the script are recorded in `run.sh`.
For more information, you can refer to:[asr1](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell/asr1)
For more information, you can refer to [asr1](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell/asr1)
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## 3.3 Inference
PP-ASR supports use `paddlespeech asr --model xxx --input xxx.wav` to use pre-trained model to do model inference after install `paddlespeech` by `pip install paddlespeech`.
PP-ASR supports use `paddlespeech asr --model xxx --input xxx.wav` to use the pre-trained model to do model inference after install `paddlespeech` by `pip install paddlespeech`.
Specific supported functions include:
- Prediction of single audio
- Use pipe to predict multiple audio
- Use the pipe to predict multiple audio
- Support RTF calculation
For specific usage, please refer to: [speech_recognition](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_recognition/README_cn.md)
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@@ -83,7 +83,7 @@ For more information about service deployment, you can refer to the aistudio tut
## 3.5 Customized Auto Speech Recognition and Deployment
For customized auto speech recognition and deployment, PP-ASR provides feature extraction(fbank) => Inference model（Scoring Library）=> C++ program of TLG（WFST, token, lexion, grammer). For specific usage, please refer to: [speechx](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx)
If you want to quickly use it, you can refer to:[custom_streaming_asr](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/custom_streaming_asr/README_cn.md)
If you want to quickly use it, you can refer to [custom_streaming_asr](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/custom_streaming_asr/README_cn.md)
For more information about customized auto speech recognition and deployment, you can refer to the aistudio tutorial:
-[Customized Auto Speech Recognition](https://aistudio.baidu.com/aistudio/projectdetail/4021561)
