A Study on Speech Recognition for Nursing Record

碩士 === 慈濟大學 === 醫學資訊學系碩士班 === 103 === The use of computers and mobile phones have been popular in the recent decade. The speech recognition function also has been integrated in the computers and mobile phones to assist use. Popular speech recognition systems such as Apple Siri, Android Google voic...

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Bibliographic Details
Main Authors: Hsu Shin-Pei, 許歆沛
Other Authors: Hsu Hong-Chun
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/55452188046915297651
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spelling ndltd-TW-103TCU006040042016-10-23T04:12:12Z http://ndltd.ncl.edu.tw/handle/55452188046915297651 A Study on Speech Recognition for Nursing Record 語音辨識應用於護理相關紀錄 Hsu Shin-Pei 許歆沛 碩士 慈濟大學 醫學資訊學系碩士班 103 The use of computers and mobile phones have been popular in the recent decade. The speech recognition function also has been integrated in the computers and mobile phones to assist use. Popular speech recognition systems such as Apple Siri, Android Google voice typing, Microsoft Windows 7 voice recognition, and IBM Viavoice, etc. can help to input general terms easily and the correctness is also acceptable. But for the proper noun, the recognition ability of existing systems is not enough. In this thesis, a special speech recognition system for proper noun, using in nursing records, is studied. We use the Julius system, a open source large vocabulary CSR engine developed by Kawahara lab. et.al., to develop the speech recognition system. First the HTK (Hidden Markov Model Toolkit) been used to build the acoustic model and then SRILM (Stanford Research Institute Language Modeling Toolkit) been used to establish N-Gram language mode. Finally, we integrated them by Julius system. Although the correct rate of the recognition is still not acceptable but the system may help to build similar system and to reduce the workload of nurses. Hsu Hong-Chun 許弘駿 2015 學位論文 ; thesis 44 zh-TW
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description 碩士 === 慈濟大學 === 醫學資訊學系碩士班 === 103 === The use of computers and mobile phones have been popular in the recent decade. The speech recognition function also has been integrated in the computers and mobile phones to assist use. Popular speech recognition systems such as Apple Siri, Android Google voice typing, Microsoft Windows 7 voice recognition, and IBM Viavoice, etc. can help to input general terms easily and the correctness is also acceptable. But for the proper noun, the recognition ability of existing systems is not enough. In this thesis, a special speech recognition system for proper noun, using in nursing records, is studied. We use the Julius system, a open source large vocabulary CSR engine developed by Kawahara lab. et.al., to develop the speech recognition system. First the HTK (Hidden Markov Model Toolkit) been used to build the acoustic model and then SRILM (Stanford Research Institute Language Modeling Toolkit) been used to establish N-Gram language mode. Finally, we integrated them by Julius system. Although the correct rate of the recognition is still not acceptable but the system may help to build similar system and to reduce the workload of nurses.
author2 Hsu Hong-Chun
author_facet Hsu Hong-Chun
Hsu Shin-Pei
許歆沛
author Hsu Shin-Pei
許歆沛
spellingShingle Hsu Shin-Pei
許歆沛
A Study on Speech Recognition for Nursing Record
author_sort Hsu Shin-Pei
title A Study on Speech Recognition for Nursing Record
title_short A Study on Speech Recognition for Nursing Record
title_full A Study on Speech Recognition for Nursing Record
title_fullStr A Study on Speech Recognition for Nursing Record
title_full_unstemmed A Study on Speech Recognition for Nursing Record
title_sort study on speech recognition for nursing record
publishDate 2015
url http://ndltd.ncl.edu.tw/handle/55452188046915297651
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