Low-dimensional Space Transforms of Posteriors in Speech Recognition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F10%3A00504557" target="_blank" >RIV/49777513:23520/10:00504557 - 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
Low-dimensional Space Transforms of Posteriors in Speech Recognition
Original language description
In this paper we present three novel posterior transforms with the primary goal to achieve a high reduction of a feature vector size. The presented methods transform the posteriors to 1D or 2D space. For such a high reduction ratio the usually applied methods fail to keep the discriminative information. Contrary, the presented methods were specifically designed to retain most of the discriminative information. In our experiments, we used several different combinations of feature extraction methods nowadays commonly used, i.e. the PLP features (augmented with delta and acceleration coefficients) and two kinds of MLP-ANN features: the bottleneck (BN) and posterior estimates (PE). The experiments were designed with special attention to the assessment of possible improvements of the performance when the PLP features are combined either with the BN features or with the PE features whose dimensionality was reduced using the proposed feature transforms. The performance of the designed transfo
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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