Original title: Generování fonetického slovníku pro rozpoznávání řeči z dat
Translated title: Data-driven Pronunciation Generation for ASR
Authors: Obedkova, Maria ; Plátek, Ondřej (advisor) ; Peterek, Nino (referee)
Document type: Master’s theses
Year: 2019
Language: eng
Abstract: Data-Driven Pronunciation Generation for ASR Maria Obedkova In ASR systems, dictionaries are usually used to describe pronunciations of words in a language. These dictionaries are typically hand-crafted by linguists. One of the most significant drawbacks of dictionaries created this way is that linguistically motivated pronunciations are not necessarily the optimal ones for ASR. The goal of this research was to explore approaches of data-driven pro- nunciation generation for ASR. We investigated several approaches of lexicon generation and implemented the completely new data-driven solution based on the pronunciation clustering. We proposed an approach for feature extraction and researched different unsupervised methods for pronunciation clustering. We evaluated the proposed approach and compared it with the current hand-crafted dictionary. The proposed data-driven approach could beat the established base- lines but underperformed in comparison to the hand-crafted dictionary which could be due to unsatisfactory features extracted from data or insufficient fine tuning. 1
Keywords: ASR; data-driven; phonetic dictionary; phonetics; unsupervised; ASR; data-driven; fonetický slovník; fonetika

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/109402

Permalink: http://www.nusl.cz/ntk/nusl-404999


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Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses