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This paper presents a speech synthesis system for Amharic language and describes and how the important prosodic features of the language were modeled in the system. The developed Amharic Text-to-Speech system (AmhTTS) is parametric and rule-based that employs a cepstral method. The system uses a source filter model for speech production and a Log Magnitude(More)
Developing correct Grapheme-to-Phoneme (GTP) conversion method is a central problem in text-to-speech synthesis. Particularly, deriving phonologi-cal features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation but neither is shown in orthography. This paper(More)
This paper reports preliminary results of data-driven decision tree based segmental duration prediction for Amharic Text-to-speech synthesis system. Using a manually annotated speech corpus, we extracted a limited number of important features for the construction of training and testing sets. Then, a decision tree based segmental duration prediction was(More)
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