Do Joint Language-Audio Embeddings Encode Perceptual Timbre Semantics?

• URL: http://arxiv.org/abs/2510.14249v1
• Date: Thu, 16 Oct 2025 03:01:41 GMT
• Title: Do Joint Language-Audio Embeddings Encode Perceptual Timbre Semantics?
• Authors: Qixin Deng, Bryan Pardo, Thrasyvoulos N Pappas,
• Abstract summary: We evaluate the above three joint language-audio embedding models on their ability to capture perceptual dimensions of timbre.<n>Our findings show that LAION-CLAP consistently provides the most reliable alignment with human-perceived timbre semantics across both instrumental sounds and audio effects.
• Score: 10.420650470020844
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Understanding and modeling the relationship between language and sound is critical for applications such as music information retrieval,text-guided music generation, and audio captioning. Central to these tasks is the use of joint language-audio embedding spaces, which map textual descriptions and auditory content into a shared embedding space. While multimodal embedding models such as MS-CLAP, LAION-CLAP, and MuQ-MuLan have shown strong performance in aligning language and audio, their correspondence to human perception of timbre, a multifaceted attribute encompassing qualities such as brightness, roughness, and warmth, remains underexplored. In this paper, we evaluate the above three joint language-audio embedding models on their ability to capture perceptual dimensions of timbre. Our findings show that LAION-CLAP consistently provides the most reliable alignment with human-perceived timbre semantics across both instrumental sounds and audio effects.

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