Exploring the role of phonetic bottleneck features for speaker and language recognition
Using bottleneck features extracted from a deep neural network (DNN) trained to predict senone posteriors has resulted in new, state-of-the-art technology for language and speaker identification. For language identification, the features' dense phonetic information is believed to enable improve...
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| Autores principales: | McLaren, M., Ferrer, L., Lawson, A., The Institute of Electrical and Electronics Engineers Signal Processing Society |
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| Formato: | CONF |
| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_15206149_v2016-May_n_p5575_McLaren |
| Aporte de: |
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