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huolongshe 41866ad471 | 2 months ago | |
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app | 8 months ago | |
docs | 8 months ago | |
fun_text_processing | 8 months ago | |
.gitignore | 8 months ago | |
Dockerfile | 8 months ago | |
LICENSE | 8 months ago | |
README.md | 2 months ago | |
application.yml | 8 months ago | |
build-docker.sh | 8 months ago | |
pack_model.py | 8 months ago | |
pip-install-reqs.sh | 8 months ago | |
requirements.txt | 8 months ago | |
run_model_server.py | 8 months ago |
英语逆文本正则化模型是基于 FunTextProcessing 开源代码库生成,用于英语语音识别模型结果后处理中的逆文本正则化部分。
逆文本正则化(Inverse Text Normalization)和文本正则化(Text Normalization)是语音交互系统中必不可少的部分。逆文本正则化(ITN)广泛应用于语音识别结果的文本后处理模块,实现从口语域到书面域的文字的转换,使显示的文字更加符合人的阅读习惯。文本正则化(TN)广泛用于语音合成系统的前端数据处理。
模型来源: https://modelscope.cn/models/damo/speech_inverse_text_processing_fun-text-processing-itn-en/summary
本模型基于 ServiceBoot微服务引擎 进行服务化封装,参见: 《CubeAI模型开发指南》
$ sh pip-install-reqs.sh
$ serviceboot start
或
$ python3 run_model_server.py
一键式本地容器化部署和运行,参见: 《CubeAI模型独立部署指南》 或 CubeAI Docker Builder
本模型服务可一键发布至 CubeAI智立方平台 进行共享和部署,参见: 《CubeAI模型发布指南》
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》