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

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.

Fabrication and Characterization of Nylon 66/PAN Nanofibrous Film Used as Separator of Lithium-Ion Battery.

In recent years, portable electronic devices have flourished, and the safety of lithium batteries has received increasing attention. In this study, nanofibers were prepared by electrospinning using different ratios of nylon 66/polyacrylonitrile (PAN), and their properties were studied and compared with commercial PP separators. The experimental results show that the addition of PAN in nylon 66/PAN nanofibrous film used as separator of lithium-ion battery can enhance the porosity up to 85%. There is also no significant shrinkage in the shrinkage test, and the thermal dimensional stability is good. When the Li/LiFePO4 lithium battery is prepared by nylon 66/PAN nanofibrous film used as separator, the capacitor can be maintained at 140 mAhg-1 after 20 cycles at 0.1 C, and the coulombic efficiency is still maintained at 99%, which has excellent electrochemical performance.