Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке:
https://open.uns.ac.rs/handle/123456789/2154
Назив: | Whispered speech recognition using hidden markov models and support vector machines | Аутори: | Galić, Jovan Popović, Branislav Pavlović, Dragana |
Датум издавања: | 1-јан-2018 | Часопис: | Acta Polytechnica Hungarica | Сажетак: | © 2018, Budapest Tech Polytechnical Institution. All rights reserved. Whisper is a specific mode of speech characterized by turbulent airflow at the glottis level. Despite an increased effort in speech perception, the intelligibility of whisper in human communication is very high. An enormous acoustic mismatch between normally phonated (neutral) and whispered speech is the main reason why modern Automatic Speech Recognition (ASR) systems have significant drop of performances when applied to whisper. In this paper, we present an analysis in recognition of whisper using 2 machine-learning techniques: Hidden Markov Models (HMM) and Support Vector Machines (SVM). The experiments are conducted in both Speaker Dependent (SD) and Speaker Independent (SI) fashion for Whi-Spe speech database. The best neutral-trained whisper recognition accuracy in SD fashion (83.36%) is obtained in SVM framework. At the same time, HMM-based recognition gave the highest recognition accuracy in SI fashion (87.42%). The results in recognition of neutral speech are given as well. | URI: | https://open.uns.ac.rs/handle/123456789/2154 | ISSN: | 17858860 | DOI: | 10.12700/APH.15.5.2018.5.2 |
Налази се у колекцијама: | FTN Publikacije/Publications |
Приказати целокупан запис ставки
SCOPUSTM
Навођења
7
проверено 20.11.2023.
Преглед/и станица
13
Протекла недеља
9
9
Протекли месец
0
0
проверено 03.05.2024.
Google ScholarTM
Проверите
Алт метрика
Ставке на DSpace-у су заштићене ауторским правима, са свим правима задржаним, осим ако није другачије назначено.