Spoken term detection for Kazakh language

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The paper presents a spoken term detection system for Kazakh language in which significant improvements are obtained through modifying speech-to-text process used for generating word- based lattices. These lattices are indexed and used for the keyword search later. Spoken Term Detection systems quickly discover the occurrence of a term, which might be just a word or sequence of words, in a large audio set of heterogeneous speech records. The paper provides an overview of a speech-to-text and keyword search system architecture built primarily on the top of the Kaldi toolkit and expands on a few highlights. Our aim was to develop a general system pipeline which could be advanced regarding phonological and linguistic features of Kazakh language in order to detect OOV keywords.
Original languageEnglish
Title of host publicationThe 4-th International Conference on Computer Processing of Turkic Languages “TurkLang 2016”
Place of PublicationBishkek, Kyrgyz Republic
Pages47
Number of pages52
Publication statusPublished - Aug 2016

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Keywords

  • Speech Retrieval, Lattice Indexing, Spoken Term Detection, Speech Recognition, Keyword Search

Cite this

Kozhirbayev, Z., Karabalayeva, M., & Yessenbayev, Z. (2016). Spoken term detection for Kazakh language. In The 4-th International Conference on Computer Processing of Turkic Languages “TurkLang 2016” (pp. 47).