کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6960730 1452003 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Intonation modelling using a muscle model and perceptually weighted matching pursuit
ترجمه فارسی عنوان
مدل سازی هوش مصنوعی با استفاده از یک مدل عضلانی و دنباله یابی متناسب با وزن
کلمات کلیدی
مدل سازی هوشمند، پیگیری تطبیقی، فیزیولوژی، همبستگی وزنی، سنتز متن به گفتار،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
We propose a physiologically based intonation model using perceptual relevance. Motivated by speech synthesis from a speech-to-speech translation (S2ST) point of view, we aim at a language independent way of modelling intonation. The model presented in this paper can be seen as a generalisation of the command response (CR) model, albeit with the same modelling power. It is an additive model which decomposes intonation contours into a sum of critically damped system impulse responses. To decompose the intonation contour, we use a weighted correlation based atom decomposition algorithm (WCAD) built around a matching pursuit framework. The algorithm allows for an arbitrary precision to be reached using an iterative procedure that adds more elementary atoms to the model. Experiments are presented demonstrating that this generalised CR (GCR) model is able to model intonation as would be expected. Experiments also show that the model produces a similar number of parameters or elements as the CR model. We conclude that the GCR model is appropriate as an engineering solution for modelling prosody, and hope that it is a contribution to a deeper scientific understanding of the neurobiological process of intonation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Speech Communication - Volume 97, March 2018, Pages 81-93
نویسندگان
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