TY - JOUR
AU - 
AB - ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ, ИНЖЕНЕРИЯ ДАННЫХ И ЗНАНИЙ _____________________________________________ DOI 10.15622/sp.60.8 S.B. SUZIĆ, T.V. DELIĆ, S.J. OSTROGONAC, S.V. ĐURIĆ, D.J. PEKAR STYLE-CODE METHOD FOR MULTI-STYLE PARAMETRIC TEXT-TO-SPEECH SYNTESIS Suzić S.B., Delić T.V., Ostrogonac S.J., Đurić S.V., Pekar D.J. Style-Code Method for Multi-Style Parametric Text-to-Speech Synthesis. Abstract. Modern text-to-speech systems generally achieve good intelligibility. The one of the main drawbacks of these systems is the lack of expressiveness in comparison to natural human speech. It is very unpleasant when automated system conveys positive and negative message in completely the same way. The introduction of parametric methods in speech synthesis gave possibility to easily change speaker characteristics and speaking styles. In this paper a simple method for incorporating styles into synthesized speech by using style codes is presented. The proposed method requires just a couple of minutes of target style and moderate amount of neutral speech. It is successfully applied to both hidden Markov models and deep neural networks-based synthesis, giving style code as additional input to the model. Listening tests confirmed that better style expressiveness is achieved by deep neural networks synthesis compared to hidden Markov model synthesis. It is also proved that quality of speech synthesized by deep neural networks in 
TI - Style-Code Method for Multi-Style Parametric Text-to-Speech Synthesis
JO - SPIIRAS Proceedings
DO - 10.15622/sp.60.8
DA - 2018-10-01
UR - https://www.deepdyve.com/lp/unpaywall/style-code-method-for-multi-style-parametric-text-to-speech-synthesis-9pvig7yPyl
DP - DeepDyve
ER -