175 citations · 494 across the 44 of their papers we have counts for
16 papers · 1 filter
The second multi-channel multi-party meeting transcription challenge (M2MeT) 2.0): A benchmark for speaker-attributed ASR
Yuhao Liang, Mohan Shi, Fan Yu +11
With the success of the first Multi-channel Multi-party Meeting Transcription challenge (M2MeT), the second M2MeT challenge (M2MeT 2.0) held in ASRU2023 particularly aims to tackle…
Emphasized Non-Target Speaker Knowledge in Knowledge Distillation for Automatic Speaker Verification
Duc-Tuan Truong, Ruijie Tao, Jia Qi Yip +2
Knowledge distillation (KD) is used to enhance automatic speaker verification performance by ensuring consistency between large teacher networks and lightweight student networks at…
Speaker-Aware Anti-Spoofing
Xuechen Liu, Md Sahidullah, Kong Aik Lee +1
We address speaker-aware anti-spoofing, where prior knowledge of the target speaker is incorporated into a voice spoofing countermeasure (CM). In contrast to the frequently used sp…
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…
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…
ASVspoof 2021: Towards Spoofed and Deepfake Speech Detection in the Wild
Xuechen Liu, Xin Wang, Md Sahidullah +8
Benchmarking initiatives support the meaningful comparison of competing solutions to prominent problems in speech and language processing. Successive benchmarking evaluations typic…
Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion
Hye-jin Shim, Hemlata Tak, Xuechen Liu +12
Deep learning has brought impressive progress in the study of both automatic speaker verification (ASV) and spoofing countermeasures (CM). Although solutions are mutually dependent…
Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge
Fan Yu, Shiliang Zhang, Pengcheng Guo +13
The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand Challenge (M2MeT) focuses on one of the most valuable and the most challenging scenarios of speech technologie…
MFA: TDNN with Multi-scale Frequency-channel Attention for Text-independent Speaker Verification with Short Utterances
Tianchi Liu, Rohan Kumar Das, Kong Aik Lee +1
The time delay neural network (TDNN) represents one of the state-of-the-art of neural solutions to text-independent speaker verification. However, they require a large number of fi…
PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction
Yi Ma, Kong Aik Lee, Ville Hautamaki +1
Speech enhancement aims to improve the perceptual quality of the speech signal by suppression of the background noise. However, excessive suppression may lead to speech distortion…
Task-aware Warping Factors in Mask-based Speech Enhancement
Qiongqiong Wang, Kong Aik Lee, Takafumi Koshinaka +2
This paper proposes the use of two task-aware warping factors in mask-based speech enhancement (SE). One controls the balance between speech-maintenance and noise-removal in traini…
Serialized Multi-Layer Multi-Head Attention for Neural Speaker Embedding
Hongning Zhu, Kong Aik Lee, Haizhou Li
This paper proposes a serialized multi-layer multi-head attention for neural speaker embedding in text-independent speaker verification. In prior works, frame-level features from o…
Multi-Level Transfer Learning from Near-Field to Far-Field Speaker Verification
Li Zhang, Qing Wang, Kong Aik Lee +2
In far-field speaker verification, the performance of speaker embeddings is susceptible to degradation when there is a mismatch between the conditions of enrollment and test speech…
Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing
Tomi Kinnunen, Andreas Nautsch, Md Sahidullah +6
Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behavio…
Introduction to Voice Presentation Attack Detection and Recent Advances
Md Sahidullah, Hector Delgado, Massimiliano Todisco +4
Over the past few years significant progress has been made in the field of presentation attack detection (PAD) for automatic speaker recognition (ASV). This includes the developmen…
Attention Mechanism in Speaker Recognition: What Does It Learn in Deep Speaker Embedding?
Qiongqiong Wang, Koji Okabe, Kong Aik Lee +2
This paper presents an experimental study on deep speaker embedding with an attention mechanism that has been found to be a powerful representation learning technique in speaker re…