8 papers
MERaLiON-SER: Robust Speech Emotion Recognition Model for English and SEA Languages
Hardik B. Sailor, Aw Ai Ti, Chen Fang Yih Nancy +26
We present MERaLiON-SER, a robust speech emotion recognition model designed for English and Southeast Asian languages. The model is trained using a hybrid objective combining weigh…
Incorporating Contextual Paralinguistic Understanding in Large Speech-Language Models
Qiongqiong Wang, Hardik B. Sailor, Jeremy H. M. Wong +6
Current large speech language models (Speech-LLMs) often exhibit limitations in empathetic reasoning, primarily due to the absence of training datasets that integrate both contextu…
ASTAR-NTU solution to AudioMOS Challenge 2025 Track1
Fabian Ritter-Gutierrez, Yi-Cheng Lin, Jui-Chiang Wei +3
Evaluation of text-to-music systems is constrained by the cost and availability of collecting experts for assessment. AudioMOS 2025 Challenge track 1 is created to automatically pr…
A correlation-permutation approach for speech-music encoders model merging
Fabian Ritter-Gutierrez, Yi-Cheng Lin, Jeremy H. M Wong +3
Creating a unified speech and music model requires expensive pre-training. Model merging can instead create an unified audio model with minimal computational expense. However, dire…
Beyond Classification: Towards Speech Emotion Reasoning with Multitask AudioLLMs
Wenyu Zhang, Yingxu He, Geyu Lin +9
Audio Large Language Models (AudioLLMs) have achieved strong results in semantic tasks like speech recognition and translation, but remain limited in modeling paralinguistic cues s…
Distilling a speech and music encoder with task arithmetic
Fabian Ritter-Gutierrez, Yi-Cheng Lin, Jui-Chiang Wei +4
Despite the progress in self-supervised learning (SSL) for speech and music, existing models treat these domains separately, limiting their capacity for unified audio understanding…