4 citations · 9 across the 15 of their papers we have counts for
9 papers · 1 filter
Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detection
Jiawen Kang, Junan Li, Jinchao Li +2
Automatic Speech Recognition (ASR) plays an important role in speech-based automatic detection of Alzheimer's disease (AD). However, recognition errors could propagate downstream,…
Improving Grapheme-to-Phoneme Conversion through In-Context Knowledge Retrieval with Large Language Models
Dongrui Han, Mingyu Cui, Jiawen Kang +3
Grapheme-to-phoneme (G2P) conversion is a crucial step in Text-to-Speech (TTS) systems, responsible for mapping grapheme to corresponding phonetic representations. However, it face…
On the Within-class Variation Issue in Alzheimer's Disease Detection
Jiawen Kang, Dongrui Han, Lingwei Meng +4
Alzheimer's Disease (AD) detection commonly employs machine learning classification models to distinguish between individuals with AD and those without. Different from conventional…
Disentangling Speakers in Multi-Talker Speech Recognition with Speaker-Aware CTC
Jiawen Kang, Lingwei Meng, Mingyu Cui +4
Multi-talker speech recognition (MTASR) faces unique challenges in disentangling and transcribing overlapping speech. To address these challenges, this paper investigates the role…
Exploring SSL Discrete Speech Features for Zipformer-based Contextual ASR
Mingyu Cui, Yifan Yang, Jiajun Deng +7
Self-supervised learning (SSL) based discrete speech representations are highly compact and domain adaptable. In this paper, SSL discrete speech features extracted from WavLM model…
Large Language Model Can Transcribe Speech in Multi-Talker Scenarios with Versatile Instructions
Lingwei Meng, Shujie Hu, Jiawen Kang +6
Recent advancements in large language models (LLMs) have revolutionized various domains, bringing significant progress and new opportunities. Despite progress in speech-related tas…
Empowering Whisper as a Joint Multi-Talker and Target-Talker Speech Recognition System
Lingwei Meng, Jiawen Kang, Yuejiao Wang +4
Multi-talker speech recognition and target-talker speech recognition, both involve transcription in multi-talker contexts, remain significant challenges. However, existing methods…
Purple-teaming LLMs with Adversarial Defender Training
Jingyan Zhou, Kun Li, Junan Li +4
Existing efforts in safeguarding LLMs are limited in actively exposing the vulnerabilities of the target LLM and readily adapting to newly emerging safety risks. To address this, w…
Cross-Speaker Encoding Network for Multi-Talker Speech Recognition
Jiawen Kang, Lingwei Meng, Mingyu Cui +4
End-to-end multi-talker speech recognition has garnered great interest as an effective approach to directly transcribe overlapped speech from multiple speakers. Current methods typ…