A Unified HMM Based Approach
Von Yitagessu B. Gebremedhin
TUDpress 2013. Kartoniert, 24 x 17 cm, 100 S., mit zahlr. s/w-Abb. u. Graf.
Amharic is the official language of Ethiopia and one of the most under-resourced languages in the world. The first part of this thesis deals with development of a syllable based ASR system for Amharic. It is demonstrated that a smaller number of acoustic models are sufficient to build a syllable based, speaker independent, continuous, Amharic ASR. It is built for weather forecast and business report applications using the UASR tool kit. A speech corpus of more than 35 hours duration was recorded in three different environments. The grammar is finite state transducer based and the lexical model consists of thousands of words. Though acoustic models for only 93 syllables are trained, a recognition accuracy of 93 % is achieved. In the second part of this thesis, development of a parametric unit selection-based speech synthesis for the Amharic language is explained. A speech corpus uttered by a single male speaker is used to train the HMMs. The final section analyzes a corpus of read Amharic speech and surveys syllable-based prosodic variations in F0, duration and intensity to develop suitable prosody models for speech synthesis and recognition.
Yitagessu Birhanu Gebremedhin studied at Bahir Dar University, Faculty of Engineering for 5 years and graduated with a bachelor of science in Electrical Engineering in 2001. After that, he worked as an instructor at Jimma University, Department of Electrical and Computer Engineering with a wide range of experience in conducting senior classes. After two years of teaching experience, he joined University of Delhi, College of Engineering in India and graduated with a master of Engineering in Computer Technology and Applications in 2005. From 2010 to 2013, he stayed at Technische Universität Dresden for research work which is summarized in this thesis.
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