From ba3a3bf4e67e861b833092d05d7c3842ea670cbc Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期二, 28 五月 2024 14:53:18 +0800
Subject: [PATCH] Add files via upload
---
README.md | 18 +++++++++++-------
1 files changed, 11 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
index 95529c6..e02b3e2 100644
--- a/README.md
+++ b/README.md
@@ -14,6 +14,7 @@
| [**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new)
| [**Installation**](#installation)
| [**Quick Start**](#quick-start)
+| [**Tutorial**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/tutorial/README.md)
| [**Runtime**](./runtime/readme.md)
| [**Model Zoo**](#model-zoo)
| [**Contact**](#contact)
@@ -27,6 +28,8 @@
<a name="whats-new"></a>
## What's new:
+- 2024/05/15锛歟motion recognition models are new supported. [emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)锛孾emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary)锛孾emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary). currently supports the following categories: 0: angry 1: happy 2: neutral 3: sad 4: unknown.
+- 2024/05/15: Offline File Transcription Service 4.5, Offline File Transcription Service of English 1.6锛孯eal-time Transcription Service 1.10 released锛宎dapting to FunASR 1.0 model structure锛�([docs](runtime/readme.md))
- 2024/03/05锛欰dded the Qwen-Audio and Qwen-Audio-Chat large-scale audio-text multimodal models, which have topped multiple audio domain leaderboards. These models support speech dialogue, [usage](examples/industrial_data_pretraining/qwen_audio).
- 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))
@@ -82,10 +85,11 @@
| 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 | 1.5G |
-| 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 | 1.5G |
-| 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 |
+| 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 |
@@ -154,7 +158,7 @@
from funasr import AutoModel
model = AutoModel(model="fsmn-vad")
-wav_file = f"{model.model_path}/example/asr_example.wav"
+wav_file = f"{model.model_path}/example/vad_example.wav"
res = model.generate(input=wav_file)
print(res)
```
@@ -207,8 +211,8 @@
res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
print(res)
```
-
-More examples ref to [docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)
+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)
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