مشاهده‌ مشخصات مقاله

Target Cost Weight Training for Unit Selection Speech Synthesis

Authors	Majid Namnabat M. Mehdi Homayounpour
Conference	دوازدهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Abstract	In recent years, the unit selection-based concatenative speech synthesis method using a large corpus has attracted great attention, as it produces more natural quality speech compared to the parameter driven models. Weights of cost functions of unit selection approach have great effect on output quality. Important proportion or weight of every feature must be determined such a manner that cost functions has suitable correlation by human perceptual. In this paper, we proposed a new approach to automatically determine optimal weights for target cost using classification and regression trees. In this method, an objective measure by suitable correlation to human perceptually is initially selected. So, for instances of every phoneme, a classification tree has build to predict objective measure. Therefore, the proportion importance of every feature in classifying data using regression trees are determined and considered as weight of this feature. The objective measure prediction has over 50% correlation using the proposed method that showed 65% improvement relation to previous methods.
قیمت	برای اعضای سایت : 100,000 Rial برای دانشجویان عضو انجمن : 20,000 Rial برای اعضای عادی انجمن : 40,000 Rial

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