From 6da6377ce465a20be5fed344241e2425fd14e167 Mon Sep 17 00:00:00 2001 From: 游雁 <zhifu.gzf@alibaba-inc.com> Date: 星期一, 20 二月 2023 10:33:55 +0800 Subject: [PATCH] readme --- README.md | 3 ++- 1 files changed, 2 insertions(+), 1 deletions(-) diff --git a/README.md b/README.md index eaeb9ba..e9c4c42 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ - We support a new feature, [grpc](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/grpc), you could build the ASR service with grpc, by deploying the modelscope pipeline or onnxruntime. - We release a new model [paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary), which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. - We optimize the timestamp alignment of [Paraformer-large-long](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), the prediction accuracy of timestamp is much improved, and achieving accumulated average shift (aas) of 74.7ms, [details](https://arxiv.org/abs/2301.12343). -- We release a new model, [8k VAD model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary), which could predict the duration of none-silence speech. It could be freely integrated with any ASR models in [modelscope](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary). +- We release a new model, [8k VAD model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary), which could predict the duration of none-silence speech. It could be freely integrated with any ASR models in [modelscope](https://github.com/alibaba-damo-academy/FunASR/discussions/134). - We release a new model, [MFCCA](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary), a multi-channel multi-speaker model which is independent of the number and geometry of microphones and supports Mandarin meeting transcription. - We release several new UniASR model: [Southern Fujian Dialect model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/summary), @@ -32,6 +32,7 @@ [Vietnamese model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online/summary), [Persian model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/summary). - We release a new model, [paraformer-data2vec model](https://www.modelscope.cn/models/damo/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/summary), an unsupervised pretraining model on AISHELL-2, which is inited for paraformer model and then finetune on AISHEL-1. +- We release a new feature, the `VAD`, `ASR` and `PUNC` models could be integrated freely, which could be models from [modelscope](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), or the local finetine models. The [demo](https://github.com/alibaba-damo-academy/FunASR/discussions/134). - Various new types of audio input types are now supported by modelscope inference pipeline, including: mp3銆乫lac銆乷gg銆乷pus... ### 2023.1.16, funasr-0.1.6锛� modelscope-1.2.0 - We release a new version model [Paraformer-large-long](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), which integrate the [VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) model, [ASR](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), -- Gitblit v1.9.1