Vo-Ve: An Explainable Voice-Vector for Speaker Identity Evaluation
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866912446831132672 |
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| author | Lee, Jaejun Lee, Kyogu |
| author_facet | Lee, Jaejun Lee, Kyogu |
| contents | In this paper, we propose Vo-Ve, a novel voice-vector embedding that captures speaker identity. Unlike conventional speaker embeddings, Vo-Ve is explainable, as it contains the probabilities of explicit voice attribute classes. Through extensive analysis, we demonstrate that Vo-Ve not only evaluates speaker similarity competitively with conventional techniques but also provides an interpretable explanation in terms of voice attributes. We strongly believe that Vo-Ve can enhance evaluation schemes across various speech tasks due to its high-level explainability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_19446 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vo-Ve: An Explainable Voice-Vector for Speaker Identity Evaluation Lee, Jaejun Lee, Kyogu Sound Audio and Speech Processing In this paper, we propose Vo-Ve, a novel voice-vector embedding that captures speaker identity. Unlike conventional speaker embeddings, Vo-Ve is explainable, as it contains the probabilities of explicit voice attribute classes. Through extensive analysis, we demonstrate that Vo-Ve not only evaluates speaker similarity competitively with conventional techniques but also provides an interpretable explanation in terms of voice attributes. We strongly believe that Vo-Ve can enhance evaluation schemes across various speech tasks due to its high-level explainability. |
| title | Vo-Ve: An Explainable Voice-Vector for Speaker Identity Evaluation |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2506.19446 |