Please use this identifier to cite or link to this item: http://saruna.mnu.edu.mv/jspui/handle/123456789/4837
Title: Dhivehi automatic speech recognition system
Authors: Hassaan, Ibrahim
އިބްރާހީމް ހައްސާން
Ifham, Mohamed
ްމުހައްމަދު އިފްހާމ
Rasheed, Adam Raaif
އާދަމް ރާއިފް ރަޝީދު
Mohamed, Yameen
ޔާމީން މޮހައްމަދު
Keywords: Speech recognition solution
Dhivehi Langauge
Language model
Acoustic model
Dhivehi phonetics
The ASR system
Number recognition
Voice pitch
Dhivehi typography
Automatic Speech Recognition
Issue Date: 18-Nov-2018
Publisher: Faculty of Engineering, Science & Technology, Maldives National University
Citation: Hassan, I., Ifham, M., Rasheed, A.R., & Mohamed, Y. (2018). Dhivehi automatic speech recognition system (Project, Faculty of Engineering Science and Technology, Maldives National University). Retrieved from saruna.mnu.edu.mv
Abstract: This report details the work done to create a speech recognition solution for Dhivehi language. The system was developed using CMUSphinx speech recognition toolkit, which requires the development of a text corpus to use as output, a phonetic dictionary (list of phonemes), a language model (probabilistic representation of word occurrences in language) and an acoustic model (mapping voice features to text). The latter two can be trained using provided audio and text data. The development of our ASR system was carried out in two phases. The first phase dealt only with numbers (covering real numbers from 0 (inclusive), up to but not including 1 trillion). The second phase dealt with the entire Dhivehi language (with exceptions: it does not support thikijehi thaana and can only pick up the common Malé dialect). The system developed during the first phase had an accuracy rate of 75% (which barely passed our set minimum acceptable rate), while the system developed during the second phase had an accuracy rate of 42.5% (which failed our set minimum acceptable rate).
URI: http://saruna.mnu.edu.mv/jspui/handle/123456789/4837
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