语解决器:终端到终端的多语言失语检测
Xuanru Zhou1, Cheol Jun Cho2, Ayati Sharma2
1Zhejiang University.
概括
语解决器是一个新的框架,用于检测语音不流利,提高准确性和可扩展性. 它处理多语言和同时出现的流利性障碍,优于现有的方法.
科学领域:
- 语音处理 语音处理
- 计算语言学计算语言学
- 人工智能的人工智能是人工智能.
背景情况:
- 目前的失流性建模依赖于非一般化的模板匹配.
- 现有的方法在不断增长的数据集和跨语言能力的情况下缺乏可扩展性.
研究的目的:
- 介绍Stutter-Solver,这是一个端到端的框架,用于准确检测失流性.
- 能够准确地记录失流的类型和时间.
- 开发一个可扩展和多语言的失语检测系统.
主要方法:
- 受到YOLO对象检测的启发,Stutter-Solver采用了一种端到端的深度学习方法.
- 引入了三种新的体 (VCTK-Pro,VCTK-Art,AISHELL3-Pro) 用于失流性模拟.
- 利用基于articulatory-encodec和TTS的方法来模拟各种失流性类型.
主要成果:
- 语解决器在所有评估的不流体中实现了最先进的性能.
- 证明精确检测失流性类型和时间.
- 在处理共同不流利性和多语言检测方面表现出有效性.
结论:
- Stutter-Solver提供了一个可扩展,准确和多语言的解决方案,用于失流性建模.
- 这种新型的机体有助于推进失流性研究.
- 开源代码和数据集促进了进一步的研究和开发.
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