Syllable-based speech recognition for Amharic

Authors:
Solomon Teferra Abate;Wolfgang Menzel
Affiliations:
Uniformity of Hamburg, Hamburg, Germany;Uniformity of Hamburg, Hamburg, Germany
Venue:
Semitic '07 Proceedings of the 2007 Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources
Year:
2007

Citing 3
Cited 1

Fundamentals of speech recognition

Fundamentals of speech recognition
Automatic generation of multiple pronunciations based on neural networks

Speech Communication
Incorporating information from syllable-length time scales into automatic speech recognition

Incorporating information from syllable-length time scales into automatic speech recognition

Using different acoustic, lexical and language modeling units for ASR of an under-resourced language - Amharic

Speech Communication

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Abstract

Amharic is the Semitic language that has the second large number of speakers after Arabic (Hayward and Richard 1999). Its writing system is syllabic with Consonant-Vowel (CV) syllable structure. Amharic orthography has more or less a one to one correspondence with syllabic sounds. We have used this feature of Amharic to develop a CV syllable-based speech recognizer, using Hidden Markov Modeling (HMM), and achieved 90.43% word recognition accuracy.