Handling Pronunciation Variation Using Hybrid Approach in Continuous, Speaker Independent Speech Recognition for Amharic
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Date
2014-10
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Addis Ababa Universiy
Abstract
The problem of modeling promllciation variation lies in accurately predicting the word
pronunciations that occur in the test material .In order to achieve this, the pronunciation variants
must first be obtained in some way or other i.e. from pronunciation data or from pre-specified
phonological rules based on linguistic knowledge.
In this study, first models was developed using canonical dictionary as a reference with total
data set of 950 sentences of which 700 for training and the remaining 250 are used for testing
model
Two models were developed using knowledge based and data driven adding variants to the
respective dictionaries. Lastly another model: hybrid approach was developed. This model is
supposed to avoid the short coming of the two models, knowledge based and data driven. In light
of this, the model developed using hybrid approach has shown better performance. The better
progress obtained is due to the fact that in case of knowledge based approach, the variant added
mayor may not really appear in the text audio. in contrary, during data driven the variants
actually appear in audio but it is very difficult to listen and identify all words with variation.
Thus the experiment undertaken in this study revealed that combining the two approaches
(hybrid) is the best way for handling pronunciation variation.
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Keywords
Speaker Independent Speech Recognition for Amharic