Duration Modelling Using Neural Networks for Hindi TTS System Considering Position of Syllable in a Word-Reference-Cited by-同舟云学术

Duration Modelling Using Neural Networks for Hindi TTS System Considering Position of Syllable in a Word

Published:2015 Issue: Volume:46 Page:60-67
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Shreekanth T.,Udayashankara V.,Chandrika M.

Publisher

Elsevier BV

Subject

General Engineering

Reference11 articles.

1. A Novel Approach to Develop Speech Database for Kannada Text-to Speech System;Ravi;International Journal on Recent Trends in Engineering & Technology,2011

2. Duration modeling of Indian Languages Hindi and Telugu;Sridhar Krishna,2009

3. Modelling Syllable Duration in Indian Languages Using Neural networks;Sreenivasa Rao,2009

4. Linguistic uses of segmental duration in English: Acoustic and perceptual evidence;Klatt,1976

5. A model of segmental duration for speech synthesis in French;Bartkova;Speech Communication,1987

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1. Identification and Extraction of Features from Malayalam Poems for Analyzing Syllable Duration Patterns;ACM Transactions on Asian and Low-Resource Language Information Processing;2023-02-28

2. Text-to-Speech Synthesis: Literature Review with an Emphasis on Malayalam Language;ACM Transactions on Asian and Low-Resource Language Information Processing;2022-01-19

3. Random Forest and AdaBoost-DT: Ensemble Machine Learning Estimators to Model Malayalam Poem Syllable Duration;Soft Computing: Theories and Applications;2022

4. An efficient adaptive artificial neural network based text to speech synthesizer for Hindi language;Multimedia Tools and Applications;2021-04-09

5. Speech Features Analysis for Tone Language Speaker Discrimination Systems;Advances in Intelligent Systems and Computing;2018