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Automatic Speech Recognition for Low-resource Languages and Accents Using Multilingual and Crosslingual Information

Vu, Ngoc Thang

This thesis explores methods to rapidly bootstrap automatic speech recognition systems for languages, which lack resources for speech and language processing. We focus on finding approaches which allow using data from multiple languages to improve the performance for those languages on different levels, such as feature extraction, acoustic modeling and language modeling. Under application aspects, this thesis also includes research work on non-native and Code-Switching speech.

Volltext §
DOI: 10.5445/IR/1000041124
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Publikationsjahr 2014
Sprache Englisch
Identifikator urn:nbn:de:swb:90-411240
KITopen-ID: 1000041124
Verlag Karlsruher Institut für Technologie (KIT)
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdaten 23.01.2014
Referent/Betreuer Prof. T. Schultz
Schlagwörter Automatic Speech Recognition for Low-resource Languages
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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