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A prototype of Indonesian dictation component for typing and formatting document using a word processor software

机译:印度尼西亚听写组件的原型,用于使用文字处理器软件对文档进行键入和格式设置

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This paper presents our work to build a dictation component in Indonesian language which can be installed to the OpenOffice Writer. The component can reduce the usage of keyboard in making and formatting document by applying an Indonesian automatic speech recognizer (ASR) to transcribe speech into text and a natural language processor to transform text to document format or command. The Indonesian ASR has two main components: an acoustic model and a language model. The acoustic model was trained based on the hidden Markov model (HMM). It was trained by using recordings of 20 native Indonesian speakers, each pronounces about 340 sentences. The total duration of the recordings was about 14.5 hours. The language model based on the n-gram model with the Witten-Bell smoothing was trained by using about 800 sentences containing the recording transcriptions and some punctuated sentences. The dictation component was evaluated for its accuracy and user experience. For a closed evaluation, from 10 participants, the component achieved 89.13% word recognition accuracy. From 10 other participants, 6 out of 10 preferred to use keyboard rather than speech to make and format document. Those 6 who still preferred to use keyboard were willing to use speech if the dictation component could conduct the job effectively and efficiently.
机译:本文介绍了我们构建印尼语听写组件的工作,该组件可以安装到OpenOffice Writer。该组件可以通过应用印度尼西亚自动语音识别器(ASR)将语音转录为文本以及使用自然语言处理器将文本转换为文档格式或命令来减少键盘在制作和格式化文档中的使用。印尼ASR具有两个主要组成部分:声学模型和语言模型。声学模型是基于隐马尔可夫模型(HMM)进行训练的。它是通过使用20位印尼语母语人士的录音进行培训的,每个录音发音约340句。记录的总持续时间约为14.5小时。通过使用包含记录转录和一些标点符号的大约800个句子来训练基于具有Witten-Bell平滑的n元语法模型的语言模型。听写组件的准确性和用户体验得到了评估。进行了封闭式评估,从10位参与者中,该组件达到了89.13%的单词识别准确率。在其他10位参与者中,十分之六的人更喜欢使用键盘而不是语音来制作和格式化文档。如果听写组件能够有效地开展工作,那6个仍偏爱使用键盘的人愿意使用语音。

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