activity
20242026
collaborators

10 papers

cs.SD2026

Towards Robust Uncertainty-Aware Speaker Modeling

Junjie Li, Yang Xiao, Kong Aik Lee

Speaker embeddings aggregate frame-level acoustic features into compact representations for speaker recognition. Recent uncertainty-aware speaker modeling approaches further charac…

eess.AS2026

QuaSR: Quality-Aware Sample Reweighting for Pacific Indigenous Speech Recognition

Yishun Li, Yang Xiao, Gongping Huang +3

Training automatic speech recognition (ASR) models for low-resource languages is challenging due to limited data and highly variable supervision quality. In particular, Pacific Ind…

cs.SD2026

Overview of ESDD2: Environment-Aware Speech and Sound Deepfake Detection Challenge

Xueping Zhang, Han Yin, Yang Xiao +4

The Environment-Aware Speech and Sound Deepfake Detection Challenge (ESDD2), held in conjunction with ICME 2026, evaluated systems for five component-level audio spoofing detection…

cs.LG2026

Titans-as-a-Layer: Test-Time Memory for Conversational Speech Emotion Recognition

Daniel Chen, Qicong Hu, Yang Xiao +2

Speech emotion recognition (SER) is commonly formulated as utterance-level classification, although conversational emotion depends on a speaker's usual vocal range and the emotiona…

eess.AS2026

Continual Adaptation for Pacific Indigenous Speech Recognition

Yang Xiao, Aso Mahmudi, Nick Thieberger +3

Speech foundation models struggle with low-resource Pacific Indigenous languages because of severe data scarcity. Furthermore, full fine-tuning risks catastrophic forgetting. To ad…

eess.AS2026

ImKWS: Test-Time Adaptation for Keyword Spotting with Class Imbalance

Hanyu Ding, Yang Xiao, Jiaheng Dong +1

Keyword spotting (KWS) identifies words for voice assistants, but environmental noise frequently reduces accuracy. Standard adaptation fixes this issue and strictly requires origin…

eess.AS2026

Activation Steering for Accent Adaptation in Large Audio Language Models

Jinuo Sun, Yang Xiao, Sung Kyun Chung +4

Accent variability remains a major source of errors in automatic speech recognition, yet most adaptation methods rely on parameter fine-tuning without understanding where accent in…

eess.AS2025

AdaKWS: Towards Robust Keyword Spotting with Test-Time Adaptation

Yang Xiao, Tianyi Peng, Yanghao Zhou +1

Spoken keyword spotting (KWS) aims to identify keywords in audio for wide applications, especially on edge devices. Current small-footprint KWS systems focus on efficient model des…

eess.AS2025

AnalyticKWS: Towards Exemplar-Free Analytic Class Incremental Learning for Small-footprint Keyword Spotting

Yang Xiao, Tianyi Peng, Rohan Kumar Das +2

Keyword spotting (KWS) offers a vital mechanism to identify spoken commands in voice-enabled systems, where user demands often shift, requiring models to learn new keywords continu…

eess.AS2024

Dark Experience for Incremental Keyword Spotting

Tianyi Peng, Yang Xiao

Spoken keyword spotting (KWS) is crucial for identifying keywords within audio inputs and is widely used in applications like Apple Siri and Google Home, particularly on edge devic…