activity
20162023
most citedASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech

175 citations · 494 across the 44 of their papers we have counts for

collaborators

50 papers

cs.SD2023★ 1 cited

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…

cs.SD2023★ 12 cited

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…

eess.AS2023

Towards single integrated spoofing-aware speaker verification embeddings

Sung Hwan Mun, Hye-jin Shim, Hemlata Tak +12

This study aims to develop a single integrated spoofing-aware speaker verification (SASV) embeddings that satisfy two aspects. First, rejecting non-target speakers' input as well a…

eess.AS2023

Generalized domain adaptation framework for parametric back-end in speaker recognition

Qiongqiong Wang, Koji Okabe, Kong Aik Lee +1

State-of-the-art speaker recognition systems comprise a speaker embedding front-end followed by a probabilistic linear discriminant analysis (PLDA) back-end. The effectiveness of t…

cs.SD2023

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…

eess.AS2023

Incorporating Uncertainty from Speaker Embedding Estimation to Speaker Verification

Qiongqiong Wang, Kong Aik Lee, Tianchi Liu

Speech utterances recorded under differing conditions exhibit varying degrees of confidence in their embedding estimates, i.e., uncertainty, even if they are extracted using the sa…

cs.SD2023

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…

eess.AS2023

Probabilistic Back-ends for Online Speaker Recognition and Clustering

Alexey Sholokhov, Nikita Kuzmin, Kong Aik Lee +1

This paper focuses on multi-enrollment speaker recognition which naturally occurs in the task of online speaker clustering, and studies the properties of different scoring back-end…

eess.AS2022

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…

eess.AS2022

Speaker recognition with two-step multi-modal deep cleansing

Ruijie Tao, Kong Aik Lee, Zhan Shi +1

Neural network-based speaker recognition has achieved significant improvement in recent years. A robust speaker representation learns meaningful knowledge from both hard and easy s…

eess.AS2022★ 1 cited

Self-Supervised Training of Speaker Encoder with Multi-Modal Diverse Positive Pairs

Ruijie Tao, Kong Aik Lee, Rohan Kumar Das +2

We study a novel neural architecture and its training strategies of speaker encoder for speaker recognition without using any identity labels. The speaker encoder is trained to ext…

cs.SD2022★ 2 cited

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…

cs.SD2022★ 5 cited

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…

cs.CL2022

The Conversational Short-phrase Speaker Diarization (CSSD) Task: Dataset, Evaluation Metric and Baselines

Gaofeng Cheng, Yifan Chen, Runyan Yang +9

The conversation scenario is one of the most important and most challenging scenarios for speech processing technologies because people in conversation respond to each other in a c…

cs.SD2022★ 1 cited

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…

eess.AS2022

Scoring of Large-Margin Embeddings for Speaker Verification: Cosine or PLDA?

Qiongqiong Wang, Kong Aik Lee, Tianchi Liu

The emergence of large-margin softmax cross-entropy losses in training deep speaker embedding neural networks has triggered a gradual shift from parametric back-ends to a simpler c…

cs.SD2022

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…

cs.SD2022

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…

cs.CL2022

Improving Contextual Coherence in Variational Personalized and Empathetic Dialogue Agents

Jing Yang Lee, Kong Aik Lee, Woon Seng Gan

In recent years, latent variable models, such as the Conditional Variational Auto Encoder (CVAE), have been applied to both personalized and empathetic dialogue generation. Prior w…

cs.CL2021

DLVGen: A Dual Latent Variable Approach to Personalized Dialogue Generation

Jing Yang Lee, Kong Aik Lee, Woon Seng Gan

The generation of personalized dialogue is vital to natural and human-like conversation. Typically, personalized dialogue generation models involve conditioning the generated respo…

cs.SD2021

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…

eess.AS2021★ 7 cited

Self-supervised Speaker Recognition with Loss-gated Learning

Ruijie Tao, Kong Aik Lee, Rohan Kumar Das +2

In self-supervised learning for speaker recognition, pseudo labels are useful as the supervision signals. It is a known fact that a speaker recognition model doesn't always benefit…

eess.AS2021

ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection

Junichi Yamagishi, Xin Wang, Massimiliano Todisco +8

ASVspoof 2021 is the forth edition in the series of bi-annual challenges which aim to promote the study of spoofing and the design of countermeasures to protect automatic speaker v…

eess.AS2021★ 131 cited

ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan

Héctor Delgado, Nicholas Evans, Tomi Kinnunen +8

The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and th…