4 citations · 9 across the 7 of their papers we have counts for
8 papers
LiteCASS: A Lightweight End-to-End Network for Real-Time Stereo Cinematic Audio Source Separation
Yuanxin Guo, Qiang Ji, Mengmei Liu +3
Cinematic audio source separation (CASS) decomposes a soundtrack into dialogue, music, and sound-effects (SFX) stems. Existing CASS methods, however, suffer from two critical limit…
Decoding the Ear: A Framework for Objectifying Expressiveness from Human Preference Through Efficient Alignment
Zhiyu Lin, Jingwen Yang, Jiale Zhao +3
Recent speech-to-speech (S2S) models generate intelligible speech but still lack natural expressiveness, largely due to the absence of a reliable evaluation metric. Existing approa…
Automatic Curation of Large-Scale, High-Quality, Multi-Category Music Source Separation Dataset
Ji Yu, Yang shuo, Xu Yuetonghui +3
Most current music source separation (MSS) methods rely on supervised learning, limited by training data quantity and quality. Though web-crawling can bring abundant data, platform…
Cross-modal Audio-visual Co-learning for Text-independent Speaker Verification
Meng Liu, Kong Aik Lee, Longbiao Wang +3
Visual speech (i.e., lip motion) is highly related to auditory speech due to the co-occurrence and synchronization in speech production. This paper investigates this correlation an…
I4U System Description for NIST SRE'20 CTS Challenge
Kong Aik Lee, Tomi Kinnunen, Daniele Colibro +23
This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's submission was resu…
Deep Spectro-temporal Artifacts for Detecting Synthesized Speech
Xiaohui Liu, Meng Liu, Lin Zhang +7
The Audio Deep Synthesis Detection (ADD) Challenge has been held to detect generated human-like speech. With our submitted system, this paper provides an overall assessment of trac…
Spoofing-Aware Attention based ASV Back-end with Multiple Enrollment Utterances and a Sampling Strategy for the SASV Challenge 2022
Chang Zeng, Lin Zhang, Meng Liu +1
Current state-of-the-art automatic speaker verification (ASV) systems are vulnerable to presentation attacks, and several countermeasures (CMs), which distinguish bona fide trials…
Exploring Deep Learning for Joint Audio-Visual Lip Biometrics
Meng Liu, Longbiao Wang, Kong Aik Lee +3
Audio-visual (AV) lip biometrics is a promising authentication technique that leverages the benefits of both the audio and visual modalities in speech communication. Previous works…