مشاهده مشخصات مقاله
Target Cost Weight Training for Unit Selection Speech Synthesis
|
نویسنده (ها) |
-
Majid Namnabat
-
M. Mehdi Homayounpour
|
|
مربوط به کنفرانس |
دوازدهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
|
چکیده |
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 : ۱٠٠,٠٠٠ ریال
-
برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
-
برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
|
خرید مقاله
|
|
.gif){kind=icon}