19 citations · 24 across the 26 of their papers we have counts for
7 papers · 1 filter
LC4SV: A Denoising Framework Learning to Compensate for Unseen Speaker Verification Models
Chi-Chang Lee, Hong-Wei Chen, Chu-Song Chen +3
The performance of speaker verification (SV) models may drop dramatically in noisy environments. A speech enhancement (SE) module can be used as a front-end strategy. However, exis…
Multi-objective Non-intrusive Hearing-aid Speech Assessment Model
Hsin-Tien Chiang, Szu-Wei Fu, Hsin-Min Wang +2
Without the need for a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. While deep learning models have been used to…
Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement
Shafique Ahmed, Chia-Wei Chen, Wenze Ren +7
Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems. In this paper, we introduce a novel audio-visual SE…
The VoiceMOS Challenge 2023: Zero-shot Subjective Speech Quality Prediction for Multiple Domains
Erica Cooper, Wen-Chin Huang, Yu Tsao +3
We present the second edition of the VoiceMOS Challenge, a scientific event that aims to promote the study of automatic prediction of the mean opinion score (MOS) of synthesized an…
AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection
Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2
The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intellige…
A Study on Incorporating Whisper for Robust Speech Assessment
Ryandhimas E. Zezario, Yu-Wen Chen, Szu-Wei Fu +3
This research introduces an enhanced version of the multi-objective speech assessment model--MOSA-Net+, by leveraging the acoustic features from Whisper, a large-scaled weakly supe…
Non-Intrusive Speech Intelligibility Prediction for Hearing Aids using Whisper and Metadata
Ryandhimas E. Zezario, Fei Chen, Chiou-Shann Fuh +2
Automated speech intelligibility assessment is pivotal for hearing aid (HA) development. In this paper, we present three novel methods to improve intelligibility prediction accurac…