20 citations · 32 across the 14 of their papers we have counts for
16 papers
Audio-Conditioned Diffusion LLMs for ASR and Deliberation Processing
Mengqi Wang, Zhan Liu, Zengrui Jin +3
Diffusion-based large language models (DLLMs) have recently attracted growing interest as an alternative to autoregressive decoders. In this work, we present an empirical study on…
Investigation of Zero-shot Text-to-Speech Models for Enhancing Short-Utterance Speaker Verification
Yiyang Zhao, Shuai Wang, Guangzhi Sun +4
Short-utterance speaker verification presents significant challenges due to the limited information in brief speech segments, which can undermine accuracy and reliability. Recently…
Low-Rank and Sparse Model Merging for Multi-Lingual Speech Recognition and Translation
Qiuming Zhao, Guangzhi Sun, Chao Zhang
Language diversity presents a significant challenge in speech-to-text (S2T) tasks, such as automatic speech recognition and translation. Traditional multi-lingual multi-task traini…
SOT Triggered Neural Clustering for Speaker Attributed ASR
Xianrui Zheng, Guangzhi Sun, Chao Zhang +1
This paper introduces a novel approach to speaker-attributed ASR transcription using a neural clustering method. With a parallel processing mechanism, diarisation and ASR can be ap…
Whisper-PMFA: Partial Multi-Scale Feature Aggregation for Speaker Verification using Whisper Models
Yiyang Zhao, Shuai Wang, Guangzhi Sun +4
In this paper, Whisper, a large-scale pre-trained model for automatic speech recognition, is proposed to apply to speaker verification. A partial multi-scale feature aggregation (P…
Speaker Adaptation for Quantised End-to-End ASR Models
Qiuming Zhao, Guangzhi Sun, Chao Zhang +2
End-to-end models have shown superior performance for automatic speech recognition (ASR). However, such models are often very large in size and thus challenging to deploy on resour…
SAML: Speaker Adaptive Mixture of LoRA Experts for End-to-End ASR
Qiuming Zhao, Guangzhi Sun, Chao Zhang +2
Mixture-of-experts (MoE) models have achieved excellent results in many tasks. However, conventional MoE models are often very large, making them challenging to deploy on resource-…
CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models
Guangzhi Sun, Potsawee Manakul, Adian Liusie +4
Multimodal foundation models are prone to hallucination, generating outputs that either contradict the input or are not grounded by factual information. Given the diversity in arch…
Speech-based Slot Filling using Large Language Models
Guangzhi Sun, Shutong Feng, Dongcheng Jiang +3
Recently, advancements in large language models (LLMs) have shown an unprecedented ability across various language tasks. This paper investigates the potential application of LLMs…
Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models
Guangzhi Sun, Wenyi Yu, Changli Tang +6
Audio-visual large language models (LLM) have drawn significant attention, yet the fine-grained combination of both input streams is rather under-explored, which is challenging but…
Conditional Diffusion Model for Target Speaker Extraction
Theodor Nguyen, Guangzhi Sun, Xianrui Zheng +2
We propose DiffSpEx, a generative target speaker extraction method based on score-based generative modelling through stochastic differential equations. DiffSpEx deploys a continuou…
SALMONN: Towards Generic Hearing Abilities for Large Language Models
Changli Tang, Wenyi Yu, Guangzhi Sun +6
Hearing is arguably an essential ability of artificial intelligence (AI) agents in the physical world, which refers to the perception and understanding of general auditory informat…
Connecting Speech Encoder and Large Language Model for ASR
Wenyi Yu, Changli Tang, Guangzhi Sun +6
The impressive capability and versatility of large language models (LLMs) have aroused increasing attention in automatic speech recognition (ASR), with several pioneering studies a…
Enhancing Quantised End-to-End ASR Models via Personalisation
Qiuming Zhao, Guangzhi Sun, Chao Zhang +2
Recent end-to-end automatic speech recognition (ASR) models have become increasingly larger, making them particularly challenging to be deployed on resource-constrained devices. Mo…
Affect Recognition in Conversations Using Large Language Models
Shutong Feng, Guangzhi Sun, Nurul Lubis +3
Affect recognition, encompassing emotions, moods, and feelings, plays a pivotal role in human communication. In the realm of conversational artificial intelligence, the ability to…
Cross-Utterance Conditioned VAE for Speech Generation
Yang Li, Cheng Yu, Guangzhi Sun +8
Speech synthesis systems powered by neural networks hold promise for multimedia production, but frequently face issues with producing expressive speech and seamless editing. In res…