Text-to-speech synthesis can play an important role in interactive education and training applications, as voices for animated agents. Such agents need high-quality voices capable of expressing intent and emotion.This paper presents preliminary results in an effort aimed at synthesizing expressive military speech for training applications. Such speech has acoustic and prosodic characteristics that can differ markedly from ordinary conversational speech. A limited domain synthesis approach is used employing samples of expressive speech, classified according to speaking style. The resulting synthesizer was tested both in isolation and in the context of a virtual reality training scenario with animated characters.
Text-to-speech synthesis can play an important role in interactive education and training applications, as voices for animated agents. Such agents need high-quality voices capable of expressing intent and emotion.This paper presents preliminary results in an effort aimed at synthesizing expressive military speech for training applications. Such speech has acoustic and prosodic characteristics that can differ markedly from ordinary conversational speech. A limited domain synthesis approach is used employing samples of expressive speech, classified according to speaking style. The resulting synthesizer was tested both in isolation and in the context of a virtual reality training scenario with animated characters.
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