From a035d68e860ea6decdf422c0fc04eda4fc4de397 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=B8=B8=E9=9B=81?= Date: Mon, 15 Jan 2024 14:20:24 +0800 Subject: [PATCH] funasr1.0 --- README.md | 17 +++-------------- README_zh.md | 17 +++-------------- 2 files changed, 6 insertions(+), 28 deletions(-) diff --git a/README.md b/README.md index 50ca1832b..311439d78 100644 --- a/README.md +++ b/README.md @@ -122,13 +122,7 @@ total_chunk_num = int(len((speech)-1)/chunk_stride+1) 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(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) ``` 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. @@ -161,11 +155,7 @@ total_chunk_num = int(len((speech)-1)/chunk_stride+1) 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(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size) if len(res[0]["value"]): print(res) ``` @@ -186,8 +176,7 @@ 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")) +res = model(input=(wav_file, text_file), data_type=("sound", "text")) print(res) ``` [//]: # (FunASR supports inference and fine-tuning of models trained on industrial datasets of tens of thousands of hours. For more details, please refer to ([modelscope_egs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)). It also supports training and fine-tuning of models on academic standard datasets. For more details, please refer to([egs](https://alibaba-damo-academy.github.io/FunASR/en/academic_recipe/asr_recipe.html)). The models include speech recognition (ASR), speech activity detection (VAD), punctuation recovery, language model, speaker verification, speaker separation, and multi-party conversation speech recognition. For a detailed list of models, please refer to the [Model Zoo](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md):) diff --git a/README_zh.md b/README_zh.md index 5a489ee45..62d251b4c 100644 --- a/README_zh.md +++ b/README_zh.md @@ -119,13 +119,7 @@ total_chunk_num = int(len((speech)-1)/chunk_stride+1) 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(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) ``` @@ -160,11 +154,7 @@ total_chunk_num = int(len((speech)-1)/chunk_stride+1) 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(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size) if len(res[0]["value"]): print(res) ``` @@ -187,8 +177,7 @@ 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")) +res = model(input=(wav_file, text_file), data_type=("sound", "text")) print(res) ``` 更多详细用法（[示例](examples/industrial_data_pretraining)）