What's new:

2023.2.17, funasr-0.2.0, modelscope-1.3.0

• We support a new feature, export paraformer models into onnx and torchscripts from modelscope. The local finetuned models are also supported.
• We support a new feature, onnxruntime, you could deploy the runtime without modelscope or funasr, for the paraformer-large model, the rtf of onnxruntime is 3x speedup(0.110->0.038) on cpu, details.
• We support a new feature, grpc, you could build the ASR service with grpc, by deploying the modelscope pipeline or onnxruntime.
• We release a new model paraformer-large-contextual, 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, the prediction accuracy of timestamp is much improved, and achieving accumulated average shift (aas) of 74.7ms, details.
• We release a new model, 8k VAD model, which could predict the duration of none-silence speech. It could be freely integrated with any ASR models in modelscope.
• We release a new model, MFCCA, 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, French model, German model, Vietnamese model, Persian model.
• We release a new model, paraformer-data2vec model, 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, or the local finetine models. The demo.
• We optimize punctuation common model, enhance the recall and precision, fix the badcases of missing punctuation marks.
• Various new types of audio input types are now supported by modelscope inference pipeline, including: mp3、flac、ogg、opus...

最新更新：

• 2023年2月（2月17号发布）：funasr-0.2.0, modelscope-1.3.0

  • 功能完善：

    • 新增加模型导出功能，Modelscope中所有Paraformer模型与本地finetune模型，支持一键导出onnx格式模型与torchscripts格式模型，用于模型部署。
    • 新增加Paraformer模型onnxruntime部署功能，无须安装Modelscope与FunASR，即可部署，cpu实测，onnxruntime推理速度提升近3倍(rtf: 0.110->0.038)。
    • 新增加grpc服务功能，支持对Modelscope推理pipeline进行服务部署，也支持对onnxruntime进行服务部署。
    • 优化Paraformer-large长音频模型时间戳，对badcase时间戳预测准确率有较大幅度提升，平均首尾时间戳偏移74.7ms，详见论文。
    • 新增加任意VAD模型、ASR模型与标点模型自由组合功能，可以自由组合Modelscope中任意模型以及本地finetune后的模型进行推理，用法示例。
    • 优化标点通用模型，增加标点召回和精度，修复缺少标点等问题。
    • 新增加采样率自适应功能，任意输入采样率音频会自动匹配到模型采样率；新增加多种语音格式支持，如，mp3、flac、ogg、opus等。

  • 上线新模型：

    • Paraformer-large热词模型，可实现热词定制化，基于提供的热词列表，对热词进行激励增强，提升模型对热词的召回。
    • MFCCA多通道多说话人识别模型，与西工大音频语音与语言处理研究组合作论文，一种基于多帧跨通道注意力机制的多通道语音识别模型。
    • 8k语音端点检测VAD模型，可用于检测长语音片段中有效语音的起止时间点，支持流式输入，最小支持10ms语音输入流。
    • UniASR流式离线一体化模型: 16k UniASR闽南语、 16k UniASR法语、 16k UniASR德语、 16k UniASR越南语、 16k UniASR波斯语。
    • 基于Data2vec结构无监督预训练Paraformer模型，采用Data2vec无监督预训练初值模型，在AISHELL-1数据中finetune Paraformer模型。

New Contributors

• @zjc6666 made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/35
• @lyblsgo made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/37
• @lingyunfly made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/42
• @fangd123 made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/44
• @dyyzhmm made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/48
• @R1ckShi made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/50
• @chenmengzheAAA made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/57
• @ZhihaoDU made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/95
• @SWHL made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/97
• @yufan-aslp made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/105
• @magicharry made their first contribution in https://github.com/alibaba-damo-academy/FunASR/pull/119

Full Changelog: https://github.com/alibaba-damo-academy/FunASR/compare/v0.1.6...v0.2.0