| Paper: | ITT-P1.7 | ||
| Session: | Speech and Language Applications | ||
| Time: | Thursday, May 20, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Industry Technology Track: Speech Synthesis | ||
| Title: | MODELING SYLLABLE DURATION IN INDIAN LANGUAGES USING NEURAL NETWORKS | ||
| Authors: | Sreenivasa Rao Krothapalli; Indian Institute of Technology, Madras | ||
| Yegnanarayana B.; Indian Institute of Technology, Madras | |||
| Abstract: | In this paper we propose a neural network model for predicting the syllable duration in Indian languages. A four layer feedforward neural network trained with a backpropagation algorithm is used for modeling the syllable duration. Syllable duration prediction and analysis is performed on broadcast news data in the languages Hindi, Telugu and Tamil. The input to the network consists of a set of phonological, positional and contextual features extracted from the text. About 88% of the syllable durations are predicted within 25% of the actual duration. The relative importance of the positional and contextual features are examined separately. | ||
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