28 citations · 41 across the 15 of their papers we have counts for
15 papers
Evaluating and Improving Continual Learning in Spoken Language Understanding
Muqiao Yang, Xiang Li, Umberto Cappellazzo +2
Continual learning has emerged as an increasingly important challenge across various tasks, including Spoken Language Understanding (SLU). In SLU, its objective is to effectively h…
uSee: Unified Speech Enhancement and Editing with Conditional Diffusion Models
Muqiao Yang, Chunlei Zhang, Yong Xu +4
Speech enhancement aims to improve the quality of speech signals in terms of quality and intelligibility, and speech editing refers to the process of editing the speech according t…
Continual Contrastive Spoken Language Understanding
Umberto Cappellazzo, Enrico Fini, Muqiao Yang +3
Recently, neural networks have shown impressive progress across diverse fields, with speech processing being no exception. However, recent breakthroughs in this area require extens…
Unifying Robustness and Fidelity: A Comprehensive Study of Pretrained Generative Methods for Speech Enhancement in Adverse Conditions
Heming Wang, Meng Yu, Hao Zhang +5
Enhancing speech signal quality in adverse acoustic environments is a persistent challenge in speech processing. Existing deep learning based enhancement methods often struggle to…
DiariST: Streaming Speech Translation with Speaker Diarization
Mu Yang, Naoyuki Kanda, Xiaofei Wang +5
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and han…
SpatialCodec: Neural Spatial Speech Coding
Zhongweiyang Xu, Yong Xu, Vinay Kothapally +3
In this work, we address the challenge of encoding speech captured by a microphone array using deep learning techniques with the aim of preserving and accurately reconstructing cru…
Rethinking Voice-Face Correlation: A Geometry View
Xiang Li, Yandong Wen, Muqiao Yang +3
Previous works on voice-face matching and voice-guided face synthesis demonstrate strong correlations between voice and face, but mainly rely on coarse semantic cues such as gender…
PAAPLoss: A Phonetic-Aligned Acoustic Parameter Loss for Speech Enhancement
Muqiao Yang, Joseph Konan, David Bick +5
Despite rapid advancement in recent years, current speech enhancement models often produce speech that differs in perceptual quality from real clean speech. We propose a learning o…
TAPLoss: A Temporal Acoustic Parameter Loss for Speech Enhancement
Yunyang Zeng, Joseph Konan, Shuo Han +5
Speech enhancement models have greatly progressed in recent years, but still show limits in perceptual quality of their speech outputs. We propose an objective for perceptual quali…
Simulating realistic speech overlaps improves multi-talker ASR
Muqiao Yang, Naoyuki Kanda, Xiaofei Wang +5
Multi-talker automatic speech recognition (ASR) has been studied to generate transcriptions of natural conversation including overlapping speech of multiple speakers. Due to the di…
Improving Speech Enhancement through Fine-Grained Speech Characteristics
Muqiao Yang, Joseph Konan, David Bick +3
While deep learning based speech enhancement systems have made rapid progress in improving the quality of speech signals, they can still produce outputs that contain artifacts and…
Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
Qiqi Xiao, Jiaxu Zou, Muqiao Yang +5
Diabetic Retinopathy (DR) is a leading cause of blindness in working age adults. DR lesions can be challenging to identify in fundus images, and automatic DR detection systems can…
Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis
Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang +2
The human language can be expressed through multiple sources of information known as modalities, including tones of voice, facial gestures, and spoken language. Recent multimodal l…
Complex Transformer: A Framework for Modeling Complex-Valued Sequence
Muqiao Yang, Martin Q. Ma, Dongyu Li +2
While deep learning has received a surge of interest in a variety of fields in recent years, major deep learning models barely use complex numbers. However, speech, signal and audi…
Storing and Querying Large-Scale Spatio-Temporal Graphs with High-Throughput Edge Insertions
Mengsu Ding, Muqiao Yang, Shimin Chen
Real-world graphs often contain spatio-temporal information and evolve over time. Compared with static graphs, spatio-temporal graphs have very different characteristics, presentin…