Comparison of Depth-based Features for Lipreading

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F15%3A%230003426" target="_blank" >RIV/46747885:24220/15:#0003426 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TSP.2015.7296400" target="_blank" >http://dx.doi.org/10.1109/TSP.2015.7296400</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP.2015.7296400" target="_blank" >10.1109/TSP.2015.7296400</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of Depth-based Features for Lipreading

Popis výsledku v původním jazyce

We examine the effect of depth information captured by Microsoft Kinect on the task of visual speech recognition. We propose depth-based active appearance model (AAM) features and show improved results over discrete cosine transform (DCT). The visual anddepth features are evaluated on a database of 54 speakers each uttering 50 isolated words. In order to exploit the speech dynamics, the features are enhanced by a simplified one-stage variant of hierarchical linear discriminant analysis (Hi-LDA). In theexperiments, we consider feature fusion via combined video-depth active appearance model as a form of early integration, and compare it to traditional multi-stream hidden Markov Model as a form of decision fusion. We also perform experiments on audio-visual recognition in noisy environments and show improved results of incorporating depth information over both traditional audio-video fusion and utilization of speech enhancement algorithms.

Název v anglickém jazyce

Comparison of Depth-based Features for Lipreading

Popis výsledku anglicky

We examine the effect of depth information captured by Microsoft Kinect on the task of visual speech recognition. We propose depth-based active appearance model (AAM) features and show improved results over discrete cosine transform (DCT). The visual anddepth features are evaluated on a database of 54 speakers each uttering 50 isolated words. In order to exploit the speech dynamics, the features are enhanced by a simplified one-stage variant of hierarchical linear discriminant analysis (Hi-LDA). In theexperiments, we consider feature fusion via combined video-depth active appearance model as a form of early integration, and compare it to traditional multi-stream hidden Markov Model as a form of decision fusion. We also perform experiments on audio-visual recognition in noisy environments and show improved results of incorporating depth information over both traditional audio-video fusion and utilization of speech enhancement algorithms.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

38th International Conference on Telecommunications and Signal Processing, TSP 2015

ISBN

978-1-4799-8498-5

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

648-651

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

Praha, Česká Republika

Místo konání akce

Praha

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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