Localization in Static and Dynamic Hearing Scenarios: Utilization of Machine Learning and Binaural Auditory Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00312007" target="_blank" >RIV/68407700:21230/17:00312007 - isvavai.cz</a>
Result on the web
<a href="http://radio.feld.cvut.cz/conf/poster/proceedings/Poster_2017/Section_NS/NS_061_Koshkina.pdf" target="_blank" >http://radio.feld.cvut.cz/conf/poster/proceedings/Poster_2017/Section_NS/NS_061_Koshkina.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Localization in Static and Dynamic Hearing Scenarios: Utilization of Machine Learning and Binaural Auditory Model
Original language description
Hearing with both ears, in other words binaural hearing, allows human to localize sound sources in a space. Models of binaural hearing often simulate functions of lateral and medial superior olives (LSO and MSO), but their outputs cannot be in most cases directly mapped to certain azimuths in space. In this paper we present an azimuth classification algorithm, which utilizes both binaural models (LSO and MSO) for preprocessing of a sound signal. From their outputs features are extracted for machine learning algorithms: K-Nearest Neighbors and Artificial Neural Network. The algorithm is trained and tested on speech samples from ITU - T Rec. P501 and NOIZEUS corpora. The success of the K-NN and ANN classifiers is discussed. Both machine learning algorithms give a similar classification error in static and dynamic hearing scenarios. The error s comparable to human psychoacoustical data.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Student Scientific Conference Poster – 21/2017
ISBN
978-80-01-06153-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Czech Technical University in Prague
Place of publication
Praha
Event location
Praha
Event date
May 23, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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