Developing a Speech Synthesizer for Amharic Language Using Hidden Markov Model
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Date
2008-10
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Addis Ababa University
Abstract
Speech synthesis systems are concerned with generating a natural sounding and intelligible
Speech by taking text as input. Speech Synthesizers are very important in helping impaired
people, in teaching and learning process, for telecommunications and industries. Though it
has many applications, generating intelligible and natural sounding synthetic speech has been
a challenging task for years. To overcome these challenges, different techniques have been
studied and implemented.
Though speech synthesizers based on HMM are done for foreign languages, they are not
applicable for Amharic language since the languages special characteristics are not
considered in these synthesizers. Hence, in this thesis work Hidden Markov Model based
speech synthesis for Amharic language (HTS-FA) is done.
The HTS-FA has two phases: the training and synthesis phase. The main activities included in
the training phase are preparation of the training dataset, language modeling, feature
extraction and training the model. In the synthesis phase, models are selected according to the
text to be synthesized, and then speech parameters are generated from them. Finally, the
synthesized speech is generated from the speech parameters.
A total of five hundred sentences are used for training the model from a corpus having a size
of 11,670 sentences, and twenty sentences, which are not included in the training dataset, are
used for testing the performance of the system. In this thesis, the Mean Opinion Score (MOS)
evaluation technique is used. The results from the MOS were found to be 4.12 and 3.6 for
intelligibility and naturalness respectively for speeches synthesized by HTS-FA. Using
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concatinative method the result obtained for intelligibility and naturalness are 3.54 and 3.25
respectively.
Keywords: Speech synthesis, HMM, HMM based speech synthesis, Language Modeling
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Keywords
Speech Synthesis; HMM; HMM Based Speech Synthesis; Language Modeling