Phonetic speech segmentation of audiobooks by using adapted LSTM-based acoustic models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966127" target="_blank" >RIV/49777513:23520/22:43966127 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-22419-5_27" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-22419-5_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-22419-5_27" target="_blank" >10.1007/978-3-031-22419-5_27</a>

Result language
angličtina
Original language name
Phonetic speech segmentation of audiobooks by using adapted LSTM-based acoustic models
Original language description
This paper describes experiments on phonetic speech segmentation of audiobooks by using LSTM neural networks. The segmentation procedure includes an iterative adaptation of an initial speaker-independent model. The experimental data involves 5 audiobooks recorded by various renowned Czech speakers. About 20 minutes long portions of each audiobook were precisely manually segmented by phonetic experts. We focused mainly on the optimal setting of the iterative segmentation procedure and explored the effect of the most relevant parameters on the resulting segmentation accuracy.
Czech name
—
Czech description
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Project
<a href="/en/project/GA22-27800S" target="_blank" >GA22-27800S: Transformers of multiple modalities for more natural spoken dialog</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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