Prosodic Models of Indonesian Language: State of the Art
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Abstract
Text to Speech (TTS) is a system that synthesizes speech from text. The quality of TTS can be judged from intelligibility and naturally. Prosody is one of the parameter that can improve the quality of TTS. This study will develop a model of prosody based on information of Indonesian syntax category. Categories syntax is a word or combination of words that can be categorized as a subject, predicate, object or complement in a sentence. Prosody models developed in this study using chunking method to determine the syntax phrase category, and hidden Markov models (HMM) to predict the curve templates that match the input range of syntax phrase category. The hidden state of HMM declared by the template type pitch curve, and state the type of observation is expressed by the phrase syntax. Template pitch curve is developed by combining theory and models of prosodic pitch contours Fujisaki. Prosody generation method to convert the template pitch curve into phoneme codes, duration and pitch values for each input text sentence pitch contour representing speech.
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Keywords: Phrosody; Text to Speech; phrase; pitch; Hidden Markov Model
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