Phonetic posteriorgram-based voice conversion system to improve speech intelligibility of dysarthric patients

Wei Zhong Zheng, Ji Yan Han, Chen Kai Lee, Yu Yi Lin, Shu Han Chang, Ying Hui Lai*

*此作品的通信作者

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Background and Objective: Most dysarthric patients encounter communication problems due to unintelligible speech. Currently, there are many voice-driven systems aimed at improving their speech intelligibility; however, the intelligibility performance of these systems are affected by challenging application conditions (e.g., time variance of patient's speech and background noise). To alleviate these problems, we proposed a dysarthria voice conversion (DVC) system for dysarthric patients and investigated the benefits under challenging application conditions. Method: A deep learning-based voice conversion system with phonetic posteriorgram (PPG) features, called the DVC-PPG system, was proposed in this study. An objective-evaluation metric of Google automatic speech recognition (Google ASR) system and a listening test were used to demonstrate the speech intelligibility benefits of DVC-PPG under quiet and noisy test conditions; besides, the well-known voice conversion system using mel-spectrogram, DVC-Mels, was used for comparison to verify the benefits of the proposed DVC-PPG system. Results: The objective-evaluation metric of Google ASR showed the average accuracy of two subjects in the duplicate and outside test conditions while the DVC-PPG system provided higher speech recognitions rate (83.2% and 67.5%) than dysarthric speech (36.5% and 26.9%) and DVC-Mels (52.9% and 33.8%) under quiet conditions. However, the DVC-PPG system provided more stable performance than the DVC-Mels under noisy test conditions. In addition, the results of the listening test showed that the speech-intelligibility performance of DVC-PPG was better than those obtained via the dysarthria speech and DVC-Mels under the duplicate and outside conditions, respectively. Conclusions: The objective-evaluation metric and listening test results showed that the recognition rate of the proposed DVC-PPG system was significantly higher than those obtained via the original dysarthric speech and DVC-Mels system. Therefore, it can be inferred from our study that the DVC-PPG system can improve the ability of dysarthric patients to communicate with people under challenging application conditions.

原文English
文章編號106602
期刊Computer Methods and Programs in Biomedicine
215
DOIs
出版狀態Published - 3月 2022

指紋

深入研究「Phonetic posteriorgram-based voice conversion system to improve speech intelligibility of dysarthric patients」主題。共同形成了獨特的指紋。

引用此