Abstract
The paper describes the development of a large vocabulary continuous speech recogniser for Slovenian language with SNABI database. The problems with inflectional languages when speech recognition is performed are presented. The system is based on hidden Markov models. For acoustic modeling biphones were used whereas for language modeling bigrams and trigrams were used. To improve the recognition result and to enable fast operation of the recogniser, speaker adaptation is also used. The optimal system with the adapted acoustic model and bigram language model achieved word accuracy of 91.30% at near 10x real time. The unadapted system with the trigram language model achieved the word accuracy of 89.56%, but it was also slower than the optimal system. Its run time was 15.3x real time.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
