From 997374b88fe6b2ae5cb4dcaf47d78cb3eff09fc2 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期二, 11 六月 2024 19:56:52 +0800
Subject: [PATCH] add ctc inference code (#1806)

---
 README.md |   52 +++++++++++++++++++++++++++++++++++++++++-----------
 1 files changed, 41 insertions(+), 11 deletions(-)

diff --git a/README.md b/README.md
index e02b3e2..835eed4 100644
--- a/README.md
+++ b/README.md
@@ -2,8 +2,9 @@
 
 ([绠�浣撲腑鏂嘳(./README_zh.md)|English)
 
-# FunASR: A Fundamental End-to-End Speech Recognition Toolkit
+[//]: # (# FunASR: A Fundamental End-to-End Speech Recognition Toolkit)
 
+[![SVG Banners](https://svg-banners.vercel.app/api?type=origin&text1=FunASR馃&text2=馃挅%20A%20Fundamental%20End-to-End%20Speech%20Recognition%20Toolkit&width=800&height=210)](https://github.com/Akshay090/svg-banners)
 
 [![PyPI](https://img.shields.io/pypi/v/funasr)](https://pypi.org/project/funasr/)
 
@@ -34,6 +35,9 @@
 - 2024/03/05锛欰dded support for the Whisper-large-v3 model, a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. It can be downloaded from the[modelscope](examples/industrial_data_pretraining/whisper/demo.py), and [openai](examples/industrial_data_pretraining/whisper/demo_from_openai.py).
 - 2024/03/05: Offline File Transcription Service 4.4, Offline File Transcription Service of English 1.5锛孯eal-time Transcription Service 1.9 released锛宒ocker image supports ARM64 platform, update modelscope锛�([docs](runtime/readme.md))
 - 2024/01/30锛歠unasr-1.0 has been released ([docs](https://github.com/alibaba-damo-academy/FunASR/discussions/1319))
+
+<details><summary>Full Changelog</summary>
+
 - 2024/01/30锛歟motion recognition models are new supported. [model link](https://www.modelscope.cn/models/iic/emotion2vec_base_finetuned/summary), modified from [repo](https://github.com/ddlBoJack/emotion2vec).
 - 2024/01/25: Offline File Transcription Service 4.2, Offline File Transcription Service of English 1.3 released锛宱ptimized the VAD (Voice Activity Detection) data processing method, significantly reducing peak memory usage, memory leak optimization; Real-time Transcription Service 1.7 released锛宱ptimizatized the client-side锛�([docs](runtime/readme.md))
 - 2024/01/09: The Funasr SDK for Windows version 2.0 has been released, featuring support for The offline file transcription service (CPU) of Mandarin 4.1, The offline file transcription service (CPU) of English 1.2, The real-time transcription service (CPU) of Mandarin 1.6. For more details, please refer to the official documentation or release notes([FunASR-Runtime-Windows](https://www.modelscope.cn/models/damo/funasr-runtime-win-cpu-x64/summary))
@@ -51,22 +55,31 @@
 - 2023/07/17: BAT is released, which is a low-latency and low-memory-consumption RNN-T model. For more details, please refer to ([BAT](egs/aishell/bat)).
 - 2023/06/26: ASRU2023 Multi-Channel Multi-Party Meeting Transcription Challenge 2.0 completed the competition and announced the results. For more details, please refer to ([M2MeT2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)).
 
+</details>
 
 <a name="Installation"></a>
 ## Installation
 
+- Requirements
+```text
+python>=3.8
+torch>=1.13
+torchaudio
+```
+
+- Install for pypi
 ```shell
 pip3 install -U funasr
 ```
-Or install from source code
+- Or install from source code
 ``` sh
 git clone https://github.com/alibaba/FunASR.git && cd FunASR
 pip3 install -e ./
 ```
-Install modelscope for the pretrained models (Optional)
+- Install modelscope or huggingface_hub for the pretrained models (Optional)
 
 ```shell
-pip3 install -U modelscope
+pip3 install -U modelscope huggingface_hub
 ```
 
 ## Model Zoo
@@ -77,19 +90,19 @@
 
 |                                                                                                         Model Name                                                                                                         |                     Task Details                      |          Training Data           | Parameters |
 |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------:|:--------------------------------:|:----------:|
-|          paraformer-zh <br> ([猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)  [馃](https://huggingface.co/funasr/paraformer-tp) )           |  speech recognition, with timestamps, non-streaming   |      60000 hours, Mandarin       |    220M    |
+|          paraformer-zh <br> ([猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)  [馃](https://huggingface.co/funasr/paraformer-zh) )           |  speech recognition, with timestamps, non-streaming   |      60000 hours, Mandarin       |    220M    |
 | <nobr>paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> |             speech recognition, streaming             |      60000 hours, Mandarin       |    220M    |
 |               paraformer-en <br> ( [猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [馃](https://huggingface.co/funasr/paraformer-en) )                | speech recognition, without timestamps, non-streaming |       50000 hours, English       |    220M    |
 |                            conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃](https://huggingface.co/funasr/conformer-en) )                             |           speech recognition, non-streaming           |       50000 hours, English       |    220M    |
-|                               ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) )                               |                punctuation restoration                |    100M, Mandarin and English    |    1.1G    | 
+|                               ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) )                               |                punctuation restoration                |    100M, Mandarin and English    |    290M    | 
 |                                   fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃](https://huggingface.co/funasr/fsmn-vad) )                                   |               voice activity detection                | 5000 hours, Mandarin and English |    0.4M    | 
 |                                     fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃](https://huggingface.co/funasr/fa-zh) )                                     |                 timestamp prediction                  |       5000 hours, Mandarin       |    38M     | 
 |                                       cam++ <br> ( [猸怾(https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [馃](https://huggingface.co/funasr/campplus) )                                        |           speaker verification/diarization            |            5000 hours            |    7.2M    | 
-|                                                  Whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary)  [馃崁](https://github.com/openai/whisper) )                                                  |  speech recognition, with timestamps, non-streaming   |           multilingual           |    1550 M    |
-|                                                Whisper-large-v3 <br> ([猸怾(https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [馃崁](https://github.com/openai/whisper) )                                                 |  speech recognition, with timestamps, non-streaming   |           multilingual           |    1550 M    |
-|                                         Qwen-Audio <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio) )                                         |      audio-text multimodal models (pretraining)       |           multilingual           |  8B  |
-|                   Qwen-Audio-Chat <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                                |          audio-text multimodal models (chat)          |           multilingual           |  8B  |
-|                        emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                        |              speech emotion recongintion              |           40000 hours            |  300M  |
+|                                 Whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary)  [馃崁](https://github.com/openai/whisper) )                                  |  speech recognition, with timestamps, non-streaming   |           multilingual           |   1550 M   |
+|                                            Whisper-large-v3 <br> ([猸怾(https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [馃崁](https://github.com/openai/whisper) )                                            |  speech recognition, with timestamps, non-streaming   |           multilingual           |   1550 M   |
+|                                               Qwen-Audio <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio) )                                                |      audio-text multimodal models (pretraining)       |           multilingual           |     8B     |
+|                                        Qwen-Audio-Chat <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                        |          audio-text multimodal models (chat)          |           multilingual           |     8B     |
+|                              emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                               |              speech emotion recongintion              |           40000 hours            |    300M    |
 
 
 
@@ -153,6 +166,8 @@
 ```
 Note: `chunk_size` is the configuration for streaming latency.` [0,10,5]` indicates that the real-time display granularity is `10*60=600ms`, and the lookahead information is `5*60=300ms`. Each inference input is `600ms` (sample points are `16000*0.6=960`), and the output is the corresponding text. For the last speech segment input, `is_final=True` needs to be set to force the output of the last word.
 
+<details><summary>More Examples</summary>
+
 ### Voice Activity Detection (Non-Streaming)
 ```python
 from funasr import AutoModel
@@ -211,9 +226,24 @@
 res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
 print(res)
 ```
+
+
+### Speech Emotion Recognition
+```python
+from funasr import AutoModel
+
+model = AutoModel(model="emotion2vec_plus_large")
+
+wav_file = f"{model.model_path}/example/test.wav"
+
+res = model.generate(wav_file, output_dir="./outputs", granularity="utterance", extract_embedding=False)
+print(res)
+```
+
 More usages ref to [docs](docs/tutorial/README_zh.md), 
 more examples ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)
 
+</details>
 
 ## Export ONNX
 

--
Gitblit v1.9.1