6 citations · 14 across the 14 of their papers we have counts for
14 papers
Balancing ASR and diarization in end-to-end LLMs for multi-talker speech recognition
Naijun Zheng, Yuke Lin, Sanli Tian +4
Multi-talker speech recognition is often addressed by combining automatic speech recognition (ASR) and speaker diarization in a pipeline system. Recently, LLM-based approaches have…
The DKU System for Multi-Speaker Automatic Speech Recognition in MLC-SLM Challenge
Yuke Lin, Ming Cheng, Ze Li +1
We present the DKU system for Task 2 of the MLC-SLM Challenge, which aims to perform multi-speaker automatic speech recognition directly from raw audio without Oracle speaker label…
Diarization-Aware Multi-Speaker Automatic Speech Recognition via Large Language Models
Yuke Lin, Ming Cheng, Ze Li +2
Multi-speaker automatic speech recognition (MS-ASR) faces significant challenges in transcribing overlapped speech, a task critical for applications like meeting transcription and…
Sequence-to-Sequence Neural Diarization with Automatic Speaker Detection and Representation
Ming Cheng, Yuke Lin, Ming Li
This paper proposes a novel Sequence-to-Sequence Neural Diarization (S2SND) framework to perform online and offline speaker diarization. It is developed from the sequence-to-sequen…
VoxBlink2: A 100K+ Speaker Recognition Corpus and the Open-Set Speaker-Identification Benchmark
Yuke Lin, Ming Cheng, Fulin Zhang +3
In this paper, we provide a large audio-visual speaker recognition dataset, VoxBlink2, which includes approximately 10M utterances with videos from 110K+ speakers in the wild. This…
The Database and Benchmark for the Source Speaker Tracing Challenge 2024
Ze Li, Yuke Lin, Tian Yao +6
Voice conversion (VC) systems can transform audio to mimic another speaker's voice, thereby attacking speaker verification (SV) systems. However, ongoing studies on source speaker…
KunquDB: An Attempt for Speaker Verification in the Chinese Opera Scenario
Huali Zhou, Yuke Lin, Dong Liu +1
This work aims to promote Chinese opera research in both musical and speech domains, with a primary focus on overcoming the data limitations. We introduce KunquDB, a relatively lar…
Haha-Pod: An Attempt for Laughter-based Non-Verbal Speaker Verification
Yuke Lin, Xiaoyi Qin, Ning Jiang +2
It is widely acknowledged that discriminative representation for speaker verification can be extracted from verbal speech. However, how much speaker information that non-verbal voc…
Multi-objective Progressive Clustering for Semi-supervised Domain Adaptation in Speaker Verification
Ze Li, Yuke Lin, Ning Jiang +4
Utilizing the pseudo-labeling algorithm with large-scale unlabeled data becomes crucial for semi-supervised domain adaptation in speaker verification tasks. In this paper, we propo…
The DKU-MSXF Speaker Verification System for the VoxCeleb Speaker Recognition Challenge 2023
Ze Li, Yuke Lin, Xiaoyi Qin +3
This paper is the system description of the DKU-MSXF System for the track1, track2 and track3 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). For Track 1, we utiliz…
The DKU-MSXF Diarization System for the VoxCeleb Speaker Recognition Challenge 2023
Ming Cheng, Weiqing Wang, Xiaoyi Qin +4
This paper describes the DKU-MSXF submission to track 4 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). Our system pipeline contains voice activity detection, clust…
VoxBlink: A Large Scale Speaker Verification Dataset on Camera
Yuke Lin, Xiaoyi Qin, Guoqing Zhao +4
In this paper, we introduce a large-scale and high-quality audio-visual speaker verification dataset, named VoxBlink. We propose an innovative and robust automatic audio-visual dat…
The DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022
Xiaoyi Qin, Na Li, Yuke Lin +4
This paper is the system description of the DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC22). In this challenge, we focus on track1 and track3. For…
Laugh Betrays You? Learning Robust Speaker Representation From Speech Containing Non-Verbal Fragments
Yuke Lin, Xiaoyi Qin, Huahua Cui +2
The success of automatic speaker verification shows that discriminative speaker representations can be extracted from neutral speech. However, as a kind of non-verbal voice, laught…