40 citations · 51 across the 16 of their papers we have counts for
5 papers · 1 filter
Spatially-Augmented Sequence-to-Sequence Neural Diarization for Meetings
Li Li, Ming Cheng, Juan Liu +1
This paper proposes a Spatially-Augmented Sequence-to-Sequence Neural Diarization (SA-S2SND) framework, which integrates direction-of-arrival (DOA) cues estimated by SRP-DNN into t…
Enhancing Speaker Verification with w2v-BERT 2.0 and Knowledge Distillation guided Structured Pruning
Ze Li, Ming Cheng, Ming Li
Large-scale self-supervised Pre-Trained Models (PTMs) have shown significant improvements in the speaker verification (SV) task by providing rich feature representations. In this p…
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…
Multi-Channel Sequence-to-Sequence Neural Diarization: Experimental Results for The MISP 2025 Challenge
Ming Cheng, Fei Su, Cancan Li +2
This paper describes the speaker diarization system developed for the Multimodal Information-Based Speech Processing (MISP) 2025 Challenge. First, we utilize the Sequence-to-Sequen…