Speech-to-Speech Conversion: An Approach to Enhance the Speech Intelligibility of Dysarthric Speaker

被引：1
|
作者：
Janai, Siddhanna [1 ]
Shreekanth, T. [2 ]
Chandan, M. [3 ]
Abraham, Ajish K. [4 ]
机构：
[1] Maharaja Inst Technol, Mysore, Karnataka, India
[2] L&T Technol Serv, Vadodara, India
[3] JSS Sci & Technol Univ, Mysuru, India
[4] All India Inst Speech & Hearing, Mysore, Karnataka, India
来源：
INTERNATIONAL JOURNAL OF AMBIENT COMPUTING AND INTELLIGENCE | 2021年 / 12卷 / 01期
关键词：
All India Institute of Speech and Hearing (AIISH); Artificial Neural Networks(ANN); Automatic Speech Recognition (ASR); Linear Predictive Coding (LPC); Speech-to-Speech Conversion (STSC); Text-to-Speech (TTS); RECOGNITION;
D O I：
10.4018/IJACI.2021010108
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A novel approach to build a speech-to-speech conversion (STSC) system for individuals with speech impairment dysarthria is described. STSC system takes impaired speech having inherent disturbance as input and produces a synthesized output speech with good pronunciation and noise free utterance. The STSC system involves two stages, namely automatic speech recognition (ASR) and automatic speech synthesis. ASR transforms speech into text, while automatic speech synthesis (or text-to-speech [TTS]) performs the reverse task. At present, the recognition system is developed for a small vocabulary of 50 words and the accuracy of 94% is achieved for normal speakers and 88% for speakers with dysarthria. The output speech of TTS system has achieved a MOS value of 4.5 out of 5 as obtained by averaging the response of 20 listeners. This method of STSC would be an augmentative and alternative communication aid for speakers with dysarthria.
引用
收藏
页码：184 / 206
页数：23
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