Hugging Face Trending Papers
Vocal Music under Phoneme-Conditional Analysis
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arXiv Computation and Language
Sep 1
Vocal Music under Phoneme-Conditional Analysis
arXiv:2608.30823v1 Announce Type: cross Abstract: The vocal music of each language carries a distinctive sonic identity, even without instrumental accompaniment. We ask whether these differences are...
arXiv AI
Jul 31
MPEcho: A Melody and Phoneme-Aware Generative Framework for Controllable Cover Song Generation
arXiv:2607. 26698v1 Announce Type: cross Abstract: Cover song generation (CSG) should preserve the melodic and linguistic content of a reference song while recreating the remaining musical components.
arXiv Machine Learning
Jun 26
Listening Like a Judge: A Music-Aware Framework for Automatic Singing Performance Evaluation
arXiv:2606. 26451v1 Announce Type: cross Abstract: Automatic singing quality assessment (SQA) requires evaluating lyrical correctness and musical fidelity while handling expressive variations.
arXiv AI
Jul 8
From Textural Counterpoint to Feature Encoding: A Multi-Dimensional Machine Representation Study of Haydn's "The Lark" Integrating Electroacoustic Analysis
arXiv:2607. 05902v1 Announce Type: cross Abstract: Chamber music, as a highly precise multi-part interactive system, contains a logic of "role assignment and dynamic interaction" that provides an extremely valuable blueprint for exploring human-computer collaborative composition paradigms.
arXiv AI
Jun 6
UniVoice: A Unified Model for Speech and Singing Voice Generation
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arXiv Computation and Language
3d ago
Don't CLAP: Are Music-Text Models Bag-of-Words?
The paper evaluates whether music‑text models truly capture fine‑grained musical meaning by introducing attribute‑swap perturbations that exchange properties such as timbre or order between instruments in a caption. Four contrastive models and one large audio‑language model were tested to see if they would score higher on the original caption than on the perturbed one. The results show that none of the contrastive models reliably distinguish the captions, and the audio‑language model’s advantage stems mainly from language priors, indicating that CLAP scores behave like a bag‑of‑words and fail to reflect attribute bindings.