NDLI: High quality text-to-speech synthesis system with efficient duration models developed using coding schemes based on vowel production characteristics

Content Provider	IEEE Xplore Digital Library
Author	Reddy, V.R. Rao, K.S.
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Technol., Indian Inst. of Technol., Kharagpur, Kharagpur, India (Rao, K.S.) \|\| TCS Innovation Labs., Kolkata, India (Reddy, V.R.)
Abstract	This paper explores encoding schemes based on production characteristics of vowels. The performance of coding schemes is analyzed for accurate prediction of durations of syllables using neural network models. Linguistic and production constraints represented by positional, contextual, phonological and articulatory (PCPA) features are used for predicting the durations of syllables. These features are coded with distinct numerical values before feeding to the neural network for building models. The evaluation of coding schemes is carried out by means of objective and subjective measures. The quality of text-to-speech synthesis system is observed to be better by incorporating the duration model with vowels coded based on lip roundness.
Starting Page	7
Ending Page	12
File Size	524708
Page Count	6
File Format	PDF
e-ISBN	9781479935161
DOI	10.1109/ISDA.2013.6920727
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-08
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Laboratories Artificial neural networks Predictive models Encoding Articulation of vowels Production constraints TTS Coding scheme Neural networks Duration models Numerical models Production of speech sounds Linguistic constraints
Content Type	Text
Resource Type	Article

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