11 citations · 26 across the 14 of their papers we have counts for
14 papers · 1 filter
AdaLTM: Adaptive Layer-wise Task Vector Merging for Categorical Speech Emotion Recognition with ASR Knowledge Integration
Chia-Yu Lee, Huang-Cheng Chou, Tzu-Quan Lin +4
Integrating Automatic Speech Recognition (ASR) into Speech Emotion Recognition (SER) enhances modeling by providing linguistic context. However, conventional feature fusion faces p…
Revisiting Modeling and Evaluation Approaches in Speech Emotion Recognition: Considering Subjectivity of Annotators and Ambiguity of Emotions
Huang-Cheng Chou, Chi-Chun Lee
Over the past two decades, speech emotion recognition (SER) has received growing attention. To train SER systems, researchers collect emotional speech databases annotated by crowds…
The MSP-Podcast Corpus
Carlos Busso, Reza Lotfian, Kusha Sridhar +9
The availability of large, high-quality emotional speech databases is essential for advancing speech emotion recognition (SER) in real-world scenarios. However, many existing datab…
Do You Hear What I Mean? Quantifying the Instruction-Perception Gap in Instruction-Guided Expressive Text-To-Speech Systems
Yi-Cheng Lin, Huang-Cheng Chou, Tzu-Chieh Wei +2
Instruction-guided text-to-speech (ITTS) enables users to control speech generation through natural language prompts, offering a more intuitive interface than traditional TTS. Howe…
DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment
Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25
We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…
EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition
Yi-Cheng Lin, Huang-Cheng Chou, Yu-Hsuan Li Liang +1
Speech emotion recognition (SER) systems often exhibit gender bias. However, the effectiveness and robustness of existing debiasing methods in such multi-label scenarios remain und…
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition
Yun-Shao Tsai, Yi-Cheng Lin, Huang-Cheng Chou +1
Bias in speech emotion recognition (SER) systems often stems from spurious correlations between speaker characteristics and emotional labels, leading to unfair predictions across d…
Mitigating Subgroup Disparities in Multi-Label Speech Emotion Recognition: A Pseudo-Labeling and Unsupervised Learning Approach
Yi-Cheng Lin, Huang-Cheng Chou, Hung-yi Lee
While subgroup disparities and performance bias are increasingly studied in computational research, fairness in categorical Speech Emotion Recognition (SER) remains underexplored.…
Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning
Liang-Yeh Shen, Shi-Xin Fang, Yi-Cheng Lin +2
This paper introduces Meta-PerSER, a novel meta-learning framework that personalizes Speech Emotion Recognition (SER) by adapting to each listener's unique way of interpreting emot…
Improving Speech Emotion Recognition in Under-Resourced Languages via Speech-to-Speech Translation with Bootstrapping Data Selection
Hsi-Che Lin, Yi-Cheng Lin, Huang-Cheng Chou +1
Speech Emotion Recognition (SER) is a crucial component in developing general-purpose AI agents capable of natural human-computer interaction. However, building robust multilingual…
Stimulus Modality Matters: Impact of Perceptual Evaluations from Different Modalities on Speech Emotion Recognition System Performance
Huang-Cheng Chou, Haibin Wu, Hung-yi Lee +1
Speech Emotion Recognition (SER) systems rely on speech input and emotional labels annotated by humans. However, various emotion databases collect perceptional evaluations in diffe…
EMO-Codec: An In-Depth Look at Emotion Preservation capacity of Legacy and Neural Codec Models With Subjective and Objective Evaluations
Wenze Ren, Yi-Cheng Lin, Huang-Cheng Chou +5
The neural codec model reduces speech data transmission delay and serves as the foundational tokenizer for speech language models (speech LMs). Preserving emotional information in…
Emo-bias: A Large Scale Evaluation of Social Bias on Speech Emotion Recognition
Yi-Cheng Lin, Haibin Wu, Huang-Cheng Chou +2
The rapid growth of Speech Emotion Recognition (SER) has diverse global applications, from improving human-computer interactions to aiding mental health diagnostics. However, SER m…
EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Haibin Wu, Huang-Cheng Chou, Kai-Wei Chang +5
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop E…