2,195 research outputs found
Development of a speech recognition system for Spanish broadcast news
This paper reports on the development process of a speech recognition system for Spanish broadcast news within the MESH FP6 project. The system uses the SONIC recognizer developed at the Center for Spoken Language Research (CSLR), University of Colorado. Acoustic and language models were trained using Hub4 broadcast news data. Experiments and evaluation results are reported
Homograph Disambiguation Through Selective Diacritic Restoration
Lexical ambiguity, a challenging phenomenon in all natural languages, is
particularly prevalent for languages with diacritics that tend to be omitted in
writing, such as Arabic. Omitting diacritics leads to an increase in the number
of homographs: different words with the same spelling. Diacritic restoration
could theoretically help disambiguate these words, but in practice, the
increase in overall sparsity leads to performance degradation in NLP
applications. In this paper, we propose approaches for automatically marking a
subset of words for diacritic restoration, which leads to selective homograph
disambiguation. Compared to full or no diacritic restoration, these approaches
yield selectively-diacritized datasets that balance sparsity and lexical
disambiguation. We evaluate the various selection strategies extrinsically on
several downstream applications: neural machine translation, part-of-speech
tagging, and semantic textual similarity. Our experiments on Arabic show
promising results, where our devised strategies on selective diacritization
lead to a more balanced and consistent performance in downstream applications.Comment: accepted in WANLP 201
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