XANE Background Acoustic Embeddings: Ablation and Clustering Analysis
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917715448430592 |
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| author | Sharma, Dushyant Fosburgh, James Dumpala, Sri Harsha Sastri, Chandramouli Shama Kruchinin, Stanislav Yu. Naylor, Patrick A. |
| author_facet | Sharma, Dushyant Fosburgh, James Dumpala, Sri Harsha Sastri, Chandramouli Shama Kruchinin, Stanislav Yu. Naylor, Patrick A. |
| contents | We explore the recently proposed explainable acoustic neural embedding~(XANE) system that models the background acoustics of a speech signal in a non-intrusive manner. The XANE embeddings are used to estimate specific parameters related to the background acoustic properties of the signal which allows the embeddings to be explainable in terms of those parameters. We perform ablation studies on the XANE system and show that estimating all acoustic parameters jointly has an overall positive effect. Furthermore, we illustrate the value of XANE embeddings by performing clustering experiments on unseen test data and show that the proposed embeddings achieve a mean F1 score of 92\% for three different tasks, outperforming significantly the WavLM based signal embeddings and are complimentary to speaker embeddings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_06342 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | XANE Background Acoustic Embeddings: Ablation and Clustering Analysis Sharma, Dushyant Fosburgh, James Dumpala, Sri Harsha Sastri, Chandramouli Shama Kruchinin, Stanislav Yu. Naylor, Patrick A. Audio and Speech Processing We explore the recently proposed explainable acoustic neural embedding~(XANE) system that models the background acoustics of a speech signal in a non-intrusive manner. The XANE embeddings are used to estimate specific parameters related to the background acoustic properties of the signal which allows the embeddings to be explainable in terms of those parameters. We perform ablation studies on the XANE system and show that estimating all acoustic parameters jointly has an overall positive effect. Furthermore, we illustrate the value of XANE embeddings by performing clustering experiments on unseen test data and show that the proposed embeddings achieve a mean F1 score of 92\% for three different tasks, outperforming significantly the WavLM based signal embeddings and are complimentary to speaker embeddings. |
| title | XANE Background Acoustic Embeddings: Ablation and Clustering Analysis |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2407.06342 |