What is the impact of incorporating explicit prosodic feature representations (e.g., pitch, energy, rhythm) on

Abstract

Abstract: Speech inherently contains rich acoustic information that extends far beyond the textual language. In real-world spoken language understanding, effective interpretation often requires integrating semantic meaning (e.g., content), paralinguistic features (e.g., emotions, speed, pitch) and phonological characteristics (e.g., prosody, intonation, rhythm), which are embedded in speech. While recent multimodal Speech Large Language Models (SpeechLLMs) have demonstrated remarkable capabilities in processing audio information, their ability to perform fine-grained perception and complex reasoning in

Research Question

What is the impact of incorporating explicit prosodic feature representations (e.g., pitch, energy, rhythm) on the downstream performance of multimodal LLMs, as measured by improvements in accuracy or F1 scores on the MMSU prosody-related tasks?

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