Using morphemes in language modeling and automatic speech recognition of Amharic. (April 2014)

• Record Type: Journal Article
• Authors: TACHBELIE, MARTHA YIFIRU; ABATE, SOLOMON TEFERRA; MENZEL, WOLFGANG
• Is Part Of: Natural language engineering. Volume 20:Part 2(2014)
• Page Start: 235
• Page End: 259
• Publication Date: 2014-04
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324912000356
• Languages: English
• ISSNs: 1351-3249

Abstract

<abstract abstract-type="normal"> <title>Abstract</title> <p>This paper presents morpheme-based language models developed for Amharic (a morphologically rich Semitic language) and their application to a speech recognition task. A substantial reduction in the out of vocabulary rate has been observed as a result of using subwords or morphemes. Thus a severe problem of morphologically rich languages has been addressed. Moreover, lower perplexity values have been obtained with morpheme-based language models than with word-based models. However, when comparing the quality based on the probability assigned to the test sets, word-based models seem to fare better. We have studied the utility of morpheme-based language models in speech recognition systems and found that the performance of a relatively small vocabulary (5k) speech recognition system improved significantly as a result of using morphemes as language modeling and dictionary units. However, as the size of the vocabulary increases (20k or more) the morpheme-based systems suffer from acoustic confusability and did not achieve a significant improvement over a word-based system with an equivalent vocabulary size even with the use of higher order (quadrogram) n-gram language models.</p> </abstract>