docs and GPU memory release

游雁

2023-07-14 579afd6ac81570438c7e95164333155a9cca163c

docs and GPU memory release

 README.md

@@ -14,13 +14,13 @@
[**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new) 
| [**Highlights**](#highlights)
| [**Installation**](#installation)
| [**Usage**](#usage)
| [**Papers**](https://github.com/alibaba-damo-academy/FunASR#citations)
| [**Runtime**](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime)
| [**Model Zoo**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md)
| [**Quick Start**](#quick-start)
| [**Runtime**](./funasr/runtime/readme.md)
| [**Model Zoo**](./docs/model_zoo/modelscope_models.md)
| [**Contact**](#contact)
| [**M2MET2.0 Challenge**](https://github.com/alibaba-damo-academy/FunASR#multi-channel-multi-party-meeting-transcription-20-m2met20-challenge)


<a name="whats-new"></a>
## What's new: 

### FunASR runtime-SDK
@@ -36,11 +36,13 @@

For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases)

<a name="highlights"></a>
## Highlights
- FunASR is a fundamental speech recognition toolkit that offers a variety of features, including speech recognition (ASR), Voice Activity Detection (VAD), Punctuation Restoration, Language Models, Speaker Verification, Speaker diarization and multi-talker ASR.
- We have released a vast collection of academic and industrial pretrained models on the [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), which can be accessed through our [Model Zoo](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md). The representative [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model has achieved SOTA performance in many speech recognition tasks. 
- FunASR offers a user-friendly pipeline for fine-tuning pretrained models from the [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition). Additionally, the optimized dataloader in FunASR enables faster training speeds for large-scale datasets. This feature enhances the efficiency of the speech recognition process for researchers and practitioners.

<a name="Installation"></a>
## Installation

Install from pip
@@ -70,7 +72,8 @@

For more details, please ref to [installation](https://alibaba-damo-academy.github.io/FunASR/en/installation/installation.html)

## Usage
<a name="quick-start"></a>
## Quick Start

You could use FunASR by:

@@ -120,6 +123,8 @@
#python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "8,8,4" --audio_in "./data/wav.scp" --output_dir "./results"
```
More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/runtime/websocket_python.html#id2)

<a name="contact"></a>
## Contact

If you have any questions about FunASR, please contact us by

 README_zh.md

@@ -201,7 +201,7 @@


## 许可协议
项目遵循[The MIT License](https://opensource.org/licenses/MIT)开源协议. 工业模型许可协议请参考（[点击此处](./MODEL_LICENSE)）
项目遵循[The MIT License](https://opensource.org/licenses/MIT)开源协议。 工业模型许可协议请参考（[点击此处](./MODEL_LICENSE)）


## Stargazers over time

 funasr/bin/asr_inference_launch.py

@@ -439,6 +439,7 @@
        logging.info(rtf_avg)
        if writer is not None:
            ibest_writer["rtf"]["rtf_avf"] = rtf_avg
        torch.cuda.empty_cache()
        return asr_result_list

    return _forward
@@ -730,6 +731,7 @@
                    ibest_writer["time_stamp"][key] = "{}".format(time_stamp_postprocessed)

            logging.info("decoding, utt: {}, predictions: {}".format(key, text_postprocessed_punc))
        torch.cuda.empty_cache()
        return asr_result_list

    return _forward

 funasr/bin/vad_inference_launch.py

@@ -123,7 +123,7 @@
                vad_results.append(item)
                if writer is not None:
                    ibest_writer["text"][keys[i]] = "{}".format(results[i])

        torch.cuda.empty_cache()
        return vad_results

    return _forward

 funasr/version.txt

@@ -1 +1 @@
0.6.9
0.7.0