10 papers
Unlocking Cognitive Capabilities and Analyzing the Perception-Logic Trade-off
Longyin Zhang, Shuo Sun, Yingxu He +15
Recent advancements in Multimodal Large Language Models (MLLMs) pursue omni-perception capabilities, yet integrating robust sensory grounding with complex reasoning remains a chall…
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…
Benchmarking Contextual and Paralinguistic Reasoning in Speech-LLMs: A Case Study with In-the-Wild Data
Qiongqiong Wang, Hardik Bhupendra Sailor, Tianchi Liu +7
Recent speech-LLMs have shown impressive performance in tasks like transcription and translation, yet they remain limited in understanding the paralinguistic aspects of speech cruc…
Interpolating Speaker Identities in Embedding Space for Data Expansion
Tianchi Liu, Ruijie Tao, Qiongqiong Wang +5
The success of deep learning-based speaker verification systems is largely attributed to access to large-scale and diverse speaker identity data. However, collecting data from more…
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…
Contextual Paralinguistic Data Creation for Multi-Modal Speech-LLM: Data Condensation and Spoken QA Generation
Qiongqiong Wang, Hardik B. Sailor, Tianchi Liu +1
Current speech-LLMs exhibit limited capability in contextual reasoning alongside paralinguistic understanding, primarily due to the lack of Question-Answer (QA) datasets that cover…