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Speech, Audio, Image and Biomedical Signal Processing using Neural Networks pp 71–95Cite as

Modeling Supra-Segmental Features of Syllables Using Neural Networks

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 83))

In this chapter we discuss modeling of supra-segmental features (intonation and duration) of syllables, and suggest some applications of these models. These supra-segmental features are also termed as prosodic features, and hence the corresponding models are known as prosody models. Neural networks are used to capture the implicit duration and intonation knowledge in the sequence of syllables of an utterance. A four layer feedforward neural network trained with backpropagation algorithm is used for modeling the duration and intonation knowledge of syllables separately. Labeled broadcast news data in the languages Hindi, Telugu and Tamil is used to develop neural network models in order to predict the duration and F0 of syllables in these languages. The input to the neural network consists of a feature vector representing the positional, contextual and phonological constraints. For improving the accuracy of prediction, further processing is done on the predicted values. We also propose a two-stage duration model for improving the accuracy of prediction. The performance of the prosody models is evaluated using objective measures such as average prediction error, standard deviation and correlation coefficient. The prosody models are examined for applications such as speaker recognition, language identification and text-to-speech synthesis.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India

    K. Sreenivasa Rao

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  1. K. Sreenivasa Rao
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Editors and Affiliations

  1. Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307, USA

    Bhanu Prasad

  2. Department of Electronics and Communication Engineering, Indian Institute of Technology Guwahati, Guwahati, India

    S. R. Mahadeva Prasanna

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Rao, K.S. (2008). Modeling Supra-Segmental Features of Syllables Using Neural Networks. In: Prasad, B., Prasanna, S.R.M. (eds) Speech, Audio, Image and Biomedical Signal Processing using Neural Networks. Studies in Computational Intelligence, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75398-8_4

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  • DOI: https://doi.org/10.1007/978-3-540-75398-8_4

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