English

ExPO: Explainable Phonetic Trait-Oriented Network for Speaker Verification

Sound 2025-01-15 v2 Artificial Intelligence Audio and Speech Processing

Abstract

In speaker verification, we use computational method to verify if an utterance matches the identity of an enrolled speaker. This task is similar to the manual task of forensic voice comparison, where linguistic analysis is combined with auditory measurements to compare and evaluate voice samples. Despite much success, we have yet to develop a speaker verification system that offers explainable results comparable to those from manual forensic voice comparison. A novel approach, Explainable Phonetic Trait-Oriented (ExPO) network, is proposed in this paper to introduce the speaker's phonetic trait which describes the speaker's characteristics at the phonetic level, resembling what forensic comparison does. ExPO not only generates utterance-level speaker embeddings but also allows for fine-grained analysis and visualization of phonetic traits, offering an explainable speaker verification process. Furthermore, we investigate phonetic traits from within-speaker and between-speaker variation perspectives to determine which trait is most effective for speaker verification, marking an important step towards explainable speaker verification. Our code is available at https://github.com/mmmmayi/ExPO.

Keywords

Cite

@article{arxiv.2501.05729,
  title  = {ExPO: Explainable Phonetic Trait-Oriented Network for Speaker Verification},
  author = {Yi Ma and Shuai Wang and Tianchi Liu and Haizhou Li},
  journal= {arXiv preprint arXiv:2501.05729},
  year   = {2025}
}

Comments

Accepted by IEEE Signal Processing Letters

R2 v1 2026-06-28T21:02:15.766Z