Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli

Sentence boundary detection (SBD) or also known as sentence breaking decides where sentences begin and end. Sentence boundary detection is necessary in many applications, such as speech summarization, video summarization, speech document indexing and retrieval. This research describes sentence bound...

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Main Author:	Ramli, Muhammad Izzad
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Response surfaces (Statistics) Web databases
Online Access:	https://ir.uitm.edu.my/id/eprint/47023/1/47023.pdf
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id	my-uitm-ir.47023
record_format	uketd_dc
spelling	my-uitm-ir.470232022-07-07T03:49:08Z Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli 2013 Ramli, Muhammad Izzad Response surfaces (Statistics) Evolutionary programming (Computer science). Genetic algorithms Web databases Sentence boundary detection (SBD) or also known as sentence breaking decides where sentences begin and end. Sentence boundary detection is necessary in many applications, such as speech summarization, video summarization, speech document indexing and retrieval. This research describes sentence boundary detection in spontaneous Malay language spoken audio. Spontaneous speech is a speech that is not planned or arranged beforehand. Related speech studies for spontaneous Malay language speech are still lacking and no work has been done on sentence boundary. Previous studies showed that combination of linguistic and acoustic approach for sentence boundary detection is able to provide better than using only one approach. However, linguistic model for Malay language is still not available, only acoustic approach is used for Malay language sentence boundary detection. Therefore, the combination of prosodic features with volume features and rate-of-speech (ROS) was proposed for sentence boundary detection of spontaneous speeches. The data used are from spontaneous speeches of Malaysian Parliament Hansard Document (MPHD). Experiments are conducted on 42 minutes of Malay language spontaneous speeches comprising of 6,413 speech and non-speech segments. Then, non-speech segments are selected as the candidates for the sentence boundary detection experimental data. The accuracy achieved for the proposed speech and non-speech detection method is 97.8% and the sentence boundary detection is 100% with false alert 19.44%. As the outcome, the proposed methods of sentence boundary detection using fusion of prosodic features, volume and rate-of-speech (ROS) and Adaboost managed to detect and label sentence boundary automatically. 2013 Thesis https://ir.uitm.edu.my/id/eprint/47023/ https://ir.uitm.edu.my/id/eprint/47023/1/47023.pdf text en public masters Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Jamil, Nursuriati (Assoc. Prof. Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Jamil, Nursuriati (Assoc. Prof. Dr.)
topic	Response surfaces (Statistics) Response surfaces (Statistics) Web databases
spellingShingle	Response surfaces (Statistics) Response surfaces (Statistics) Web databases Ramli, Muhammad Izzad Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
description	Sentence boundary detection (SBD) or also known as sentence breaking decides where sentences begin and end. Sentence boundary detection is necessary in many applications, such as speech summarization, video summarization, speech document indexing and retrieval. This research describes sentence boundary detection in spontaneous Malay language spoken audio. Spontaneous speech is a speech that is not planned or arranged beforehand. Related speech studies for spontaneous Malay language speech are still lacking and no work has been done on sentence boundary. Previous studies showed that combination of linguistic and acoustic approach for sentence boundary detection is able to provide better than using only one approach. However, linguistic model for Malay language is still not available, only acoustic approach is used for Malay language sentence boundary detection. Therefore, the combination of prosodic features with volume features and rate-of-speech (ROS) was proposed for sentence boundary detection of spontaneous speeches. The data used are from spontaneous speeches of Malaysian Parliament Hansard Document (MPHD). Experiments are conducted on 42 minutes of Malay language spontaneous speeches comprising of 6,413 speech and non-speech segments. Then, non-speech segments are selected as the candidates for the sentence boundary detection experimental data. The accuracy achieved for the proposed speech and non-speech detection method is 97.8% and the sentence boundary detection is 100% with false alert 19.44%. As the outcome, the proposed methods of sentence boundary detection using fusion of prosodic features, volume and rate-of-speech (ROS) and Adaboost managed to detect and label sentence boundary automatically.
format	Thesis
qualification_level	Master's degree
author	Ramli, Muhammad Izzad
author_facet	Ramli, Muhammad Izzad
author_sort	Ramli, Muhammad Izzad
title	Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
title_short	Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
title_full	Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
title_fullStr	Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
title_full_unstemmed	Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli
title_sort	automated sentence boundary detection for spontaneous speech in malay language / muhammad izzad ramli
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/47023/1/47023.pdf
_version_	1783734776315772928

Automated sentence boundary detection for spontaneous speech in Malay language / Muhammad Izzad Ramli

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