From 8f3930494a3f6b18981fda2b0ddf8b145b330b10 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 08 三月 2023 17:50:12 +0800
Subject: [PATCH] Update README.md
---
README.md | 4 ++--
1 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index aca9b8d..772e27a 100644
--- a/README.md
+++ b/README.md
@@ -19,7 +19,7 @@
### 2023.2.17, funasr-0.2.0, modelscope-1.3.0
- We support a new feature, export paraformer models into [onnx and torchscripts](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export) from modelscope. The local finetuned models are also supported.
-- We support a new feature, [onnxruntime](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer), you could deploy the runtime without modelscope or funasr, for the [paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model, the rtf of onnxruntime is 3x speedup(0.110->0.038) on cpu, [details](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer#speed).
+- We support a new feature, [onnxruntime](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python), you could deploy the runtime without modelscope or funasr, for the [paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model, the rtf of onnxruntime is 3x speedup(0.110->0.038) on cpu, [details](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer#speed).
- 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).
@@ -112,4 +112,4 @@
booktitle={arXiv preprint arXiv:2301.12343}
year={2023}
}
-```
\ No newline at end of file
+```
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