From 3919d7454c070702e94b149e4032e9db08d28fa3 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 22 一月 2024 15:42:45 +0800
Subject: [PATCH] Funasr1.0 (#1279)
---
README_zh.md | 55 ++++++++++++++++++++++++++++++++-----------------------
1 files changed, 32 insertions(+), 23 deletions(-)
diff --git a/README_zh.md b/README_zh.md
index 62d251b..b19e7c2 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -60,14 +60,13 @@
| 妯″瀷鍚嶅瓧 | 浠诲姟璇︽儏 | 璁粌鏁版嵁 | 鍙傛暟閲� |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------:|:------------:|:----:|
| 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]() ) | 璇煶璇嗗埆锛屽甫鏃堕棿鎴宠緭鍑猴紝闈炲疄鏃� | 60000灏忔椂锛屼腑鏂� | 220M |
-| paraformer-zh-spk <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) [馃]() ) | 鍒嗚鑹茶闊宠瘑鍒紝甯︽椂闂存埑杈撳嚭锛岄潪瀹炴椂 | 60000灏忔椂锛屼腑鏂� | 220M |
-| paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃]() ) | 璇煶璇嗗埆锛屽疄鏃� | 60000灏忔椂锛屼腑鏂� | 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]() ) | 璇煶璇嗗埆锛岄潪瀹炴椂 | 50000灏忔椂锛岃嫳鏂� | 220M |
-| paraformer-en-spk <br> ([猸怾() [馃]() ) | 璇煶璇嗗埆锛岄潪瀹炴椂 | 50000灏忔椂锛岃嫳鏂� | 220M |
-| conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃]() ) | 璇煶璇嗗埆锛岄潪瀹炴椂 | 50000灏忔椂锛岃嫳鏂� | 220M |
-| ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃]() ) | 鏍囩偣鎭㈠ | 100M锛屼腑鏂囦笌鑻辨枃 | 1.1G |
-| fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃]() ) | 璇煶绔偣妫�娴嬶紝瀹炴椂 | 5000灏忔椂锛屼腑鏂囦笌鑻辨枃 | 0.4M |
-| fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃]() ) | 瀛楃骇鍒椂闂存埑棰勬祴 | 50000灏忔椂锛屼腑鏂� | 38M |
+| paraformer-zh-spk <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) [馃]() ) | 鍒嗚鑹茶闊宠瘑鍒紝甯︽椂闂存埑杈撳嚭锛岄潪瀹炴椂 | 60000灏忔椂锛屼腑鏂� | 220M |
+| paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃]() ) | 璇煶璇嗗埆锛屽疄鏃� | 60000灏忔椂锛屼腑鏂� | 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]() ) | 璇煶璇嗗埆锛岄潪瀹炴椂 | 50000灏忔椂锛岃嫳鏂� | 220M |
+| conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃]() ) | 璇煶璇嗗埆锛岄潪瀹炴椂 | 50000灏忔椂锛岃嫳鏂� | 220M |
+| ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃]() ) | 鏍囩偣鎭㈠ | 100M锛屼腑鏂囦笌鑻辨枃 | 1.1G |
+| fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃]() ) | 璇煶绔偣妫�娴嬶紝瀹炴椂 | 5000灏忔椂锛屼腑鏂囦笌鑻辨枃 | 0.4M |
+| fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃]() ) | 瀛楃骇鍒椂闂存埑棰勬祴 | 50000灏忔椂锛屼腑鏂� | 38M |
<a name="蹇�熷紑濮�"></a>
@@ -86,12 +85,16 @@
### 闈炲疄鏃惰闊宠瘑鍒�
```python
from funasr import AutoModel
-
-model = AutoModel(model="paraformer-zh")
-# for the long duration wav, you could add vad model
-# model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc")
-
-res = model(input="asr_example_zh.wav", batch_size=64)
+# paraformer-zh is a multi-functional asr model
+# use vad, punc, spk or not as you need
+model = AutoModel(model="paraformer-zh", model_revision="v2.0.2",
+ vad_model="fsmn-vad", vad_model_revision="v2.0.2",
+ punc_model="ct-punc-c", punc_model_revision="v2.0.3",
+ # spk_model="cam++", spk_model_revision="v2.0.2",
+ )
+res = model.generate(input=f"{model.model_path}/example/asr_example.wav",
+ batch_size_s=300,
+ hotword='榄旀惌')
print(res)
```
娉細`model_hub`锛氳〃绀烘ā鍨嬩粨搴擄紝`ms`涓洪�夋嫨modelscope涓嬭浇锛宍hf`涓洪�夋嫨huggingface涓嬭浇銆�
@@ -105,7 +108,7 @@
encoder_chunk_look_back = 4 #number of chunks to lookback for encoder self-attention
decoder_chunk_look_back = 1 #number of encoder chunks to lookback for decoder cross-attention
-model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.0")
+model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.2")
import soundfile
import os
@@ -119,7 +122,7 @@
for i in range(total_chunk_num):
speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
is_final = i == total_chunk_num - 1
- res = model(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size, encoder_chunk_look_back=encoder_chunk_look_back, decoder_chunk_look_back=decoder_chunk_look_back)
+ res = model.generate(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size, encoder_chunk_look_back=encoder_chunk_look_back, decoder_chunk_look_back=decoder_chunk_look_back)
print(res)
```
@@ -132,7 +135,7 @@
model = AutoModel(model="fsmn-vad", model_revision="v2.0.2")
wav_file = f"{model.model_path}/example/asr_example.wav"
-res = model(input=wav_file)
+res = model.generate(input=wav_file)
print(res)
```
@@ -154,7 +157,7 @@
for i in range(total_chunk_num):
speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
is_final = i == total_chunk_num - 1
- res = model(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size)
+ res = model.generate(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size)
if len(res[0]["value"]):
print(res)
```
@@ -163,9 +166,9 @@
```python
from funasr import AutoModel
-model = AutoModel(model="ct-punc", model_revision="v2.0.1")
+model = AutoModel(model="ct-punc", model_revision="v2.0.2")
-res = model(input="閭ｄ粖澶╃殑浼氬氨鍒拌繖閲屽惂 happy new year 鏄庡勾瑙�")
+res = model.generate(input="閭ｄ粖澶╃殑浼氬氨鍒拌繖閲屽惂 happy new year 鏄庡勾瑙�")
print(res)
```
@@ -176,11 +179,11 @@
model = AutoModel(model="fa-zh", model_revision="v2.0.0")
wav_file = f"{model.model_path}/example/asr_example.wav"
-text_file = f"{model.model_path}/example/asr_example.wav"
-res = model(input=(wav_file, text_file), data_type=("sound", "text"))
+text_file = f"{model.model_path}/example/text.txt"
+res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
print(res)
```
-鏇村璇︾粏鐢ㄦ硶锛圼绀轰緥](examples/industrial_data_pretraining)锛�
+鏇村璇︾粏鐢ㄦ硶锛圼绀轰緥](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)锛�
<a name="鏈嶅姟閮ㄧ讲"></a>
@@ -240,4 +243,10 @@
pages={2063--2067},
doi={10.21437/Interspeech.2022-9996}
}
+@article{shi2023seaco,
+ author={Xian Shi and Yexin Yang and Zerui Li and Yanni Chen and Zhifu Gao and Shiliang Zhang},
+ title={{SeACo-Paraformer: A Non-Autoregressive ASR System with Flexible and Effective Hotword Customization Ability}},
+ year=2023,
+ journal={arXiv preprint arXiv:2308.03266(accepted by ICASSP2024)},
+}
```
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