14 papers
Towards Robust Assessment of Pathological Voices via Combined Low-Level Descriptors and Foundation Model Representations
Whenty Ariyanti, Kuan-Yu Chen, Sabato Marco Siniscalchi +2
Perceptual voice quality assessment plays a vital role in diagnosing and monitoring voice disorders. Traditional methods, such as the Consensus Auditory-Perceptual Evaluation of Vo…
AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Deepfake Detection of Frontal Face Videos
Sahibzada Adil Shahzad, Ammarah Hashmi, Yan-Tsung Peng +2
Multimodal manipulations (also known as audio-visual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of…
NeuroAMP: A Novel End-to-end General Purpose Deep Neural Amplifier for Personalized Hearing Aids
Shafique Ahmed, Ryandhimas E. Zezario, Hui-Guan Yuan +4
The prevalence of hearing aids is increasing. However, optimizing the amplification processes of hearing aids remains challenging due to the complexity of integrating multiple modu…
Feature Importance across Domains for Improving Non-Intrusive Speech Intelligibility Prediction in Hearing Aids
Ryandhimas E. Zezario, Sabato M. Siniscalchi, Fei Chen +2
Given the critical role of non-intrusive speech intelligibility assessment in hearing aids (HA), this paper enhances its performance by introducing Feature Importance across Domain…
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 Speech Assessment with Visual Cues
Shafique Ahmed, Ryandhimas E. Zezario, Nasir Saleem +3
Non-intrusive assessment of speech quality and intelligibility is essential when clean reference signals are unavailable. In this work, we propose a multimodal framework that integ…