4 citations · 14 across the 32 of their papers we have counts for
22 papers · 1 filter
Ontology-grounded Automatic Knowledge Graph Construction by LLM under Wikidata schema
Xiaohan Feng, Xixin Wu, Helen Meng
We propose an ontology-grounded approach to Knowledge Graph (KG) construction using Large Language Models (LLMs) on a knowledge base. An ontology is authored by generating Competen…
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,…
Devising a Set of Compact and Explainable Spoken Language Feature for Screening Alzheimer's Disease
Junan Li, Yunxiang Li, Yuren Wang +2
Alzheimer's disease (AD) has become one of the most significant health challenges in an aging society. The use of spoken language-based AD detection methods has gained prevalence d…
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…
Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains
Kun Li, Tianhua Zhang, Xixin Wu +3
Knowledge Graphs (KGs) can serve as reliable knowledge sources for question answering (QA) due to their structured representation of knowledge. Existing research on the utilization…
Speaking from Coarse to Fine: Improving Neural Codec Language Model via Multi-Scale Speech Coding and Generation
Haohan Guo, Fenglong Xie, Dongchao Yang +2
The neural codec language model (CLM) has demonstrated remarkable performance in text-to-speech (TTS) synthesis. However, troubled by ``recency bias", CLM lacks sufficient attentio…
SoCodec: A Semantic-Ordered Multi-Stream Speech Codec for Efficient Language Model Based Text-to-Speech Synthesis
Haohan Guo, Fenglong Xie, Kun Xie +4
The long speech sequence has been troubling language models (LM) based TTS approaches in terms of modeling complexity and efficiency. This work proposes SoCodec, a semantic-ordered…
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…
AudioComposer: Towards Fine-grained Audio Generation with Natural Language Descriptions
Yuanyuan Wang, Hangting Chen, Dongchao Yang +2
Current Text-to-audio (TTA) models mainly use coarse text descriptions as inputs to generate audio, which hinders models from generating audio with fine-grained control of content…
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…
SimpleSpeech 2: Towards Simple and Efficient Text-to-Speech with Flow-based Scalar Latent Transformer Diffusion Models
Dongchao Yang, Rongjie Huang, Yuanyuan Wang +5
Scaling Text-to-speech (TTS) to large-scale datasets has been demonstrated as an effective method for improving the diversity and naturalness of synthesized speech. At the high lev…
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…
Large Language Model-based FMRI Encoding of Language Functions for Subjects with Neurocognitive Disorder
Yuejiao Wang, Xianmin Gong, Lingwei Meng +2
Functional magnetic resonance imaging (fMRI) is essential for developing encoding models that identify functional changes in language-related brain areas of individuals with Neuroc…
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…
CoLM-DSR: Leveraging Neural Codec Language Modeling for Multi-Modal Dysarthric Speech Reconstruction
Xueyuan Chen, Dongchao Yang, Dingdong Wang +3
Dysarthric speech reconstruction (DSR) aims to transform dysarthric speech into normal speech. It still suffers from low speaker similarity and poor prosody naturalness. In this pa…
Adaptive Query Rewriting: Aligning Rewriters through Marginal Probability of Conversational Answers
Tianhua Zhang, Kun Li, Hongyin Luo +3
Query rewriting is a crucial technique for passage retrieval in open-domain conversational question answering (CQA). It decontexualizes conversational queries into self-contained q…
UniAudio 1.5: Large Language Model-driven Audio Codec is A Few-shot Audio Task Learner
Dongchao Yang, Haohan Guo, Yuanyuan Wang +5
The Large Language models (LLMs) have demonstrated supreme capabilities in text understanding and generation, but cannot be directly applied to cross-modal tasks without fine-tunin…
SimpleSpeech: Towards Simple and Efficient Text-to-Speech with Scalar Latent Transformer Diffusion Models
Dongchao Yang, Dingdong Wang, Haohan Guo +3
In this study, we propose a simple and efficient Non-Autoregressive (NAR) text-to-speech (TTS) system based on diffusion, named SimpleSpeech. Its simpleness shows in three aspects:…
Addressing Index Collapse of Large-Codebook Speech Tokenizer with Dual-Decoding Product-Quantized Variational Auto-Encoder
Haohan Guo, Fenglong Xie, Dongchao Yang +3
VQ-VAE, as a mainstream approach of speech tokenizer, has been troubled by ``index collapse'', where only a small number of codewords are activated in large codebooks. This work pr…
Seamless Language Expansion: Enhancing Multilingual Mastery in Self-Supervised Models
Jing Xu, Minglin Wu, Xixin Wu +1
Self-supervised (SSL) models have shown great performance in various downstream tasks. However, they are typically developed for limited languages, and may encounter new languages…
Exploiting Audio-Visual Features with Pretrained AV-HuBERT for Multi-Modal Dysarthric Speech Reconstruction
Xueyuan Chen, Yuejiao Wang, Xixin Wu +4
Dysarthric speech reconstruction (DSR) aims to transform dysarthric speech into normal speech by improving the intelligibility and naturalness. This is a challenging task especiall…
UNIT-DSR: Dysarthric Speech Reconstruction System Using Speech Unit Normalization
Yuejiao Wang, Xixin Wu, Disong Wang +2
Dysarthric speech reconstruction (DSR) systems aim to automatically convert dysarthric speech into normal-sounding speech. The technology eases communication with speakers affected…