Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection
This study examines how ten different audio features, including MFCC, mel-spectrogram, chroma, and spectral contrast etc., influence speaker change detection (SCD) performance. The analysis is conducted using two unsupervised methods: Bayesian information criterion with Gaussian mixture model (BIC-G...
Tallennettuna:
| Päätekijät: | , , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2024-12-01
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| Sarja: | Applied Sciences |
| Aiheet: | |
| Linkit: | https://www.mdpi.com/2076-3417/14/24/12026 |
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