Do Joint Language-Audio Embeddings Encode Perceptual Timbre Semantics?

[2510.14249] Do Joint Language-Audio Embeddings Encode Perceptual Timbre Semantics? Skip to main content Search Submit Donate Log in Computer Science > Sound arXiv:2510.14249 (cs) [Submitted on 16 Oct 2025 ( v1 ), last revised 25 Aug 2026 (this version, v2)] Title: Do Joint Language-Audio Embeddings Encode Perceptual Timbre Semantics? Authors: Qixin Deng , Bryan Pardo , Thrasyvoulos N Pappas View PDF HTML (experimental) Abstract: Understanding and modeling the relationship between language and sound are essential for applications such as music information retrieval, text-guided music generation, and audio captioning. Central to these tasks are joint language-audio embedding spaces, which map textual descriptions and auditory content into a shared representation. Although multimodal embedding models such as MS-CLAP, LAION-CLAP, MuQ-MuLan, and OpenFLAM have shown strong performance in language-audio alignment, their correspondence to human perception of timbre, a multifaceted attribute encompassing qualities such as brightness, roughness, and warmth, remains under-explored. In this paper, we evaluate these joint language-audio embedding models in terms of their ability to capture perceptual timbre semantics. Across two complementary experiments, we find that LAION-CLAP shows relatively strong and consistent alignment with human-perceived timbre semantics across both instrumental sounds and descriptor-conditioned audio effects. At the same time, the overall strength of this alignment remains limited, suggesting that current joint language-audio embeddings capture perceptual timbre semantics only partially. We also observe that, overall, reverb-induced timbre semantics are more consistently encoded than equalization-induced timbre semantics. Subjects: Sound (cs.SD) ; Artificial Intelligence (cs.AI); Audio and Speech Processing (eess.AS) Cite as: arXiv:2510.14249 [cs.SD] (or arXiv:2510.14249v2 [cs.SD] for this version) https://doi.org/10.48550/arXiv.2510.14249 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Qixin Deng [ view email ] [v1] Thu, 16 Oct 2025 03:01:41 UTC (2,906 KB) [v2] Tue, 25 Aug 2026 08:00:41 UTC (1,313 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: cs.SD < prev | next > new | recent | 2025-10 Change to browse by: cs cs.AI eess eess.AS References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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