摘要
現今社會電腦、手機、平板盛行的年代，在輔助使用者輸入文字時，語音辨識是一個相當重要的功能。目前市面上的語音辨識系統，包括Siri、Android系統、Windows 7的語音辨識、IBMViavoice等等，在進行一般用語的語音辨識時，準確率相當高，但一旦加入專有名詞時，則易誤辨別為一般用語。本論文在討論建立一套屬於護理相關語音系統，方便輔助護理人員使用，及減少他們的負擔。我們利用HTK tools建立聲學模型，接著利用SRILM（Stanford Research Institute LanguageModeling Toolkit）建立N-Gram語言模型，接著將兩者進行結合後，使用Julius為解碼器，建立專屬於護理記錄的語言模型，以方便護理人員使用。
並列摘要
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 paper, 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.
延伸閱讀
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