What Are They Doing? Joint Audio-Speech Co-Reasoning

• URL: http://arxiv.org/abs/2409.14526v1
• Date: Sun, 22 Sep 2024 16:45:57 GMT
• Title: What Are They Doing? Joint Audio-Speech Co-Reasoning
• Authors: Yingzhi Wang, Pooneh Mousavi, Artem Ploujnikov, Mirco Ravanelli,
• Abstract summary: Recent Auditory Large Language Models (ALLMs) have made it possible to process audio and speech simultaneously within a single model. We introduce Joint Audio-Speech Co-Reasoning (JASCO), a novel task that unifies audio and speech processing. We establish a joint audio-speech benchmark to evaluate the joint reasoning capability of popular ALLMs.
• Score: 10.957451368533302
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In audio and speech processing, tasks usually focus on either the audio or speech modality, even when both sounds and human speech are present in the same audio clip. Recent Auditory Large Language Models (ALLMs) have made it possible to process audio and speech simultaneously within a single model, leading to further considerations of joint audio-speech tasks. In this paper, we investigate how well ALLMs can perform joint audio-speech processing. Specifically, we introduce Joint Audio-Speech Co-Reasoning (JASCO), a novel task that unifies audio and speech processing, strictly requiring co-reasoning across both modalities. We release a scene-reasoning dataset called "What Are They Doing" and establish a joint audio-speech benchmark to evaluate the joint reasoning capability of popular ALLMs. Additionally, we provide deeper insights into the models' behaviors by analyzing their dependence on each modality.

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