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October 8, 2025Open Access

Probing Audio-Generation Capabilities of Text-Based Language Models

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Authors

AAArjun Prasaath AnbazhaganPKParteek KumarUKUjjwal Kaur

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Overview

This research demonstrates LLMs can generate audio from textual prompts, suggesting avenues for improvement.

Key Points

  • LLMs can generate basic audio features, but performance declines with increased complexity, indicating limitations in their audio understanding.
  • FAD and CLAP scores are used to evaluate the quality and accuracy of audio outputs generated by large language models from text prompts.
  • Using a structured three-tier approach, this research progresses from musical notes to more complex environmental sounds and human speech.
  • Enhancements in generation techniques may improve the audio capabilities of LLMs, providing a deeper exploration into combining text and audio.

Cite This Study

Anbazhagan et al. (2025) studied this question.

synapsesocial.com/papers/68e6bc5f38ca8e474d549dbbhttps://doi.org/10.48550/arxiv.2506.00003
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  5. 5What do MLLMs hear? Examining reasoning with text and sound components in Multimodal Large Language Models2024