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20232026
most citedAVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

19 citations · 24 across the 26 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CV2024★ 1 cited

How Good is ChatGPT at Audiovisual Deepfake Detection: A Comparative Study of ChatGPT, AI Models and Human Perception

Sahibzada Adil Shahzad, Ammarah Hashmi, Yan-Tsung Peng +2

Multimodal deepfakes involving audiovisual manipulations are a growing threat because they are difficult to detect with the naked eye or using unimodal deep learningbased forgery d…

cs.CV2024

Understanding Audiovisual Deepfake Detection: Techniques, Challenges, Human Factors and Perceptual Insights

Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2

Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be…

cs.SD2024

The VoiceMOS Challenge 2024: Beyond Speech Quality Prediction

Wen-Chin Huang, Szu-Wei Fu, Erica Cooper +5

We present the third edition of the VoiceMOS Challenge, a scientific initiative designed to advance research into automatic prediction of human speech ratings. There were three tra…

eess.AS2024

Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement

Wenze Ren, Haibin Wu, Yi-Cheng Lin +7

In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction. Traditional methods, such as…

eess.AS2024

A Study on Zero-shot Non-intrusive Speech Assessment using Large Language Models

Ryandhimas E. Zezario, Sabato M. Siniscalchi, Hsin-Min Wang +1

This work investigates two strategies for zero-shot non-intrusive speech assessment leveraging large language models. First, we explore the audio analysis capabilities of GPT-4o. S…

eess.AS2024

SVSNet+: Enhancing Speaker Voice Similarity Assessment Models with Representations from Speech Foundation Models

Chun Yin, Tai-Shih Chi, Yu Tsao +1

Representations from pre-trained speech foundation models (SFMs) have shown impressive performance in many downstream tasks. However, the potential benefits of incorporating pre-tr…

cs.CV2024

Unmasking Illusions: Understanding Human Perception of Audiovisual Deepfakes

Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2

The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the in…

eess.AS2024

HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing Aids

Dyah A. M. G. Wisnu, Stefano Rini, Ryandhimas E. Zezario +2

This paper introduces HAAQI-Net, a non-intrusive deep learning-based music audio quality assessment model for hearing aid users. Unlike traditional methods like the Hearing Aid Aud…