低资源语言的User-friendly自动转录:将ESPnet插入Elpis
User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis
摘要:
本文报告的进展集成的语音识别工具包ESPnet到Elpis,一个Web前端,最初的目的是提供访问Kaldi自动语音识别工具包。这项工作的目标是使端到端的语音识别模型提供给语言工作者通过用户友好的图形界面。令人鼓舞的结果报告(i)ESPnet配方的开发用于Elpis,与先前用于训练声学模型与Persephone工具包的数据集的初步结果,以及一个新的数据集,以前没有被用于语音识别,和(ii)将ESPnet与UI增强和CUDA支持的Dockerfile一起纳入Elpis。
英文摘要:
This paper reports on progress integrating the speech recognition toolkit ESPnet into Elpis, a web front-end originally designed to provide access to the Kaldi automatic speech recognition toolkit. The goal of this work is to make end-to-end speech recognition models available to language workers via a user-friendly graphical interface. Encouraging results are reported on (i) development of an ESPnet recipe for use in Elpis, with preliminary results on data sets previously used for training acoustic models with the Persephone toolkit along with a new data set that had not previously been used in speech recognition, and (ii) incorporating ESPnet into Elpis along with UI enhancements and a CUDA-supported Dockerfile.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。