Mitsuo Komura

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This report proposes a simple and practical model for generating relatively monotonous, but su ciently natural, prosodic features by analyzing restricted natural speech. The basic assumption of this model is that the natural F0 pattern can be obtained without complicated linguistic analysis. To achieve this prosodic control, we have analyzed and modeled(More)
This report describes a method for estimating the separation degree at the bunsetsu boundary (SD) for Japanese text-to-speech synthesis. Our method gives us the prosodic symbol without using complicated linguistic analysis. First we classify bunsetsus according to the nal morpheme. Each classi ed bunsetsu has a temporary separation degree in advance. We(More)
We propose a new neural network model and its learning algorithm. The proposed neural network consists of four layers input, hidden, output and final output layers. The hidden and output layers are multiple. Using the proposed SICL(Spread Pattern Information and Cooperative Learning) algorithm, it is possible to learn analog data accurately and to obtain(More)
We have proposed the real-time QMDP method for decision making of a robot under uncertain state recognition. This method evaluates every action and chooses the best one with a particle filter for estimation and a state-value function of dynamic programming. Different from our past work, this paper applies it to a complicated decision making task that yields(More)
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