On Context-Dependent Neural Networks and Speaker Adaptation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F12%3A43916036" target="_blank" >RIV/49777513:23520/12:43916036 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
On Context-Dependent Neural Networks and Speaker Adaptation
Original language description
This paper describes evaluation of a neural network based hybrid LVCSR system. The~novelty of the evaluated hybrid system lies in speaker adaptation techniques that are employed to increase performance of neural networks for context-dependent phonetic units modeling. The performance comparison is done as follows. First, performances of different hybrid systems employing either a context-independent neural network or a context-dependent neural network are compared. Second, the influence of the recently published speaker adaptation technique called MELT is evaluated. Furthermore, several possible approaches to conversion of posterior probabilities into observation likelihoods, which are necessary for a hybrid LVSCR systems, are described and discussed inthis paper.
Czech name
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Czech description
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Project
<a href="/en/project/DF12P01OVV022" target="_blank" >DF12P01OVV022: ASR- and MT-based Access to a Large Archive of Cultural Heritage (AMALACH)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings 2012 IEEE 11th International Conference on Signal Processing
ISBN
978-1-4673-2194-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
515-518
Publisher name
IEEE Press
Place of publication
Beijing (Peking)
Event location
Beijing (Peking)
Event date
Oct 21, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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