使用低通時序列語音特徵訓練理想比率遮罩法之語音強化 (Employing Low-Pass Filtered Temporal Speech Features for the Training of Ideal Ratio Mask in Speech Enhancement)

no code implementations • IJCLCLP 2021 • Yan-Tong Chen, Jeih-weih Hung

Speech Enhancement

A Preliminary Study of the Application of Discrete Wavelet Transform Features in Conv-TasNet Speech Enhancement Model

no code implementations • ROCLING 2022 • Yan-Tong Chen, Zong-Tai Wu, Jeih-weih Hung

Nowadays, time-domain features have been widely used in speech enhancement (SE) networks like frequency-domain features to achieve excellent performance in eliminating noise from input utterances.

Speech Enhancement

Employing low-pass filtered temporal speech features for the training of ideal ratio mask in speech enhancement

no code implementations • ROCLING 2021 • Yan-Tong Chen, Zi-Qiang Lin, Jeih-weih Hung

Preliminary experiments conducted on a subset of TIMIT corpus reveal that the proposed method can make the resulting IRM achieve higher speech quality and intelligibility for the babble noise-corrupted signals compared with the original IRM, indicating that the lowpass filtered temporal feature sequence can learn a superior IRM network for speech enhancement.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2