Introducing voice timbre attribute detection

This paper focuses on explaining the timbre conveyed by speech signals and introduces a task termed voice timbre attribute detection (vTAD). In this task, voice timbre is explained with a set of sensory attributes describing its human perception. A pair of speech utterances is processed, and their intensity is compared in a designated timbre descriptor. Moreover, a framework is proposed, which is built upon the speaker embeddings extracted from the speech utterances. The investigation is conducted on the VCTK-RVA dataset. Experimental examinations on the ECAPA-TDNN and FACodec speaker encoders demonstrated that: 1) the ECAPA-TDNN speaker encoder was more capable in the seen scenario, where the testing speakers were included in the training set; 2) the FACodec speaker encoder was superior in the unseen scenario, where the testing speakers were not part of the training, indicating enhanced generalization capability. The VCTK-RVA dataset and open-source code are available on the websitethis https URL.

@article{he2025_2505.09661,
  title={ Introducing voice timbre attribute detection },
  author={ Jinghao He and Zhengyan Sheng and Liping Chen and Kong Aik Lee and Zhen-Hua Ling },
  journal={arXiv preprint arXiv:2505.09661},
  year={ 2025 }
}