Implementing a statistical method for automatic speech recognition

Speech recognition centers on the use of natural speech for human-computer interaction providing computers an ear to listen to what human beings intend to say. In addition to speech recognition as being the most natural method of communication, it offers several advantages like ease of access, speed...

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Main Authors: Gochuico, Stephany, Lee, Shirlane, Marcos, Nelson, Yu, Yau Pang
Format: text
Language:English
Published: Animo Repository 1990
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/16405
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-169182022-02-11T01:34:52Z Implementing a statistical method for automatic speech recognition Gochuico, Stephany Lee, Shirlane Marcos, Nelson Yu, Yau Pang Speech recognition centers on the use of natural speech for human-computer interaction providing computers an ear to listen to what human beings intend to say. In addition to speech recognition as being the most natural method of communication, it offers several advantages like ease of access, speed, manual freedom, and remote access. The Automatic Speech Recognition system is a prototype speaker-independent, isolated speech recognition system consisting of hardware and software components necessary in performance delivery. It was implemented using a statistical method that analyzes speech parameters to recognize sequence of words spoken by a user with pauses in-between words. Words uttered by the user are compared against the words trained and stored in the vocabulary file by computing likelihood probabilities based on speech characteristics extracted from the corresponding speech signals. The vocabulary word with the highest measure of likelihood is selected to be the most probable word uttered by the user. The accuracy of recognition depends primarily on the distinctiveness and the number of words in the vocabulary and the clarity with which the user says the words. The ASR as well as other speech recognition systems provide room for future applications. These applications include: (1) Clinical-Medical records, services for the handicapped (2) Entertainment and Education - Voice-controlled toys, interactive video games (3) Manufacturing Process Control - Machine operation, package sorting (4) Office Automation - Data entry, automatic dictation, automatic transcription and (5) Security - Voiceprint identification, building access. 1990-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/16405 Bachelor's Theses English Animo Repository Automatic speech recognition Systems software Computer design Speech processing systems
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Automatic speech recognition
Systems software
Computer design
Speech processing systems
spellingShingle Automatic speech recognition
Systems software
Computer design
Speech processing systems
Gochuico, Stephany
Lee, Shirlane
Marcos, Nelson
Yu, Yau Pang
Implementing a statistical method for automatic speech recognition
description Speech recognition centers on the use of natural speech for human-computer interaction providing computers an ear to listen to what human beings intend to say. In addition to speech recognition as being the most natural method of communication, it offers several advantages like ease of access, speed, manual freedom, and remote access. The Automatic Speech Recognition system is a prototype speaker-independent, isolated speech recognition system consisting of hardware and software components necessary in performance delivery. It was implemented using a statistical method that analyzes speech parameters to recognize sequence of words spoken by a user with pauses in-between words. Words uttered by the user are compared against the words trained and stored in the vocabulary file by computing likelihood probabilities based on speech characteristics extracted from the corresponding speech signals. The vocabulary word with the highest measure of likelihood is selected to be the most probable word uttered by the user. The accuracy of recognition depends primarily on the distinctiveness and the number of words in the vocabulary and the clarity with which the user says the words. The ASR as well as other speech recognition systems provide room for future applications. These applications include: (1) Clinical-Medical records, services for the handicapped (2) Entertainment and Education - Voice-controlled toys, interactive video games (3) Manufacturing Process Control - Machine operation, package sorting (4) Office Automation - Data entry, automatic dictation, automatic transcription and (5) Security - Voiceprint identification, building access.
format text
author Gochuico, Stephany
Lee, Shirlane
Marcos, Nelson
Yu, Yau Pang
author_facet Gochuico, Stephany
Lee, Shirlane
Marcos, Nelson
Yu, Yau Pang
author_sort Gochuico, Stephany
title Implementing a statistical method for automatic speech recognition
title_short Implementing a statistical method for automatic speech recognition
title_full Implementing a statistical method for automatic speech recognition
title_fullStr Implementing a statistical method for automatic speech recognition
title_full_unstemmed Implementing a statistical method for automatic speech recognition
title_sort implementing a statistical method for automatic speech recognition
publisher Animo Repository
publishDate 1990
url https://animorepository.dlsu.edu.ph/etd_bachelors/16405
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