Unsupervised discovery of morphemes
MPL '02 Proceedings of the ACL-02 workshop on Morphological and phonological learning - Volume 6
Morph-based speech recognition and modeling of out-of-vocabulary words across languages
ACM Transactions on Speech and Language Processing (TSLP)
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
NAACL-Demonstrations '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Demonstration Session
Morpho-syntactic post-processing of N-best lists for improved French automatic speech recognition
Computer Speech and Language
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
IEEE Transactions on Audio, Speech, and Language Processing
Applying morphological decomposition to statistical machine translation
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
State-of-the-art speech recognition technologies for Russian language
Proceedings of the 2012 Joint International Conference on Human-Centered Computer Environments
Automatic speech recognition for under-resourced languages: A survey
Speech Communication
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It is practically impossible to build a word-based lexicon for speech recognition in agglutinative languages that would cover all the relevant words. The problem is that words are generally built by concatenating several prefixes and suffixes to the word roots. Together with compounding and inflections this leads to millions of different, but still frequent word forms. Due to inflections, ambiguity and other phenomena, it is also not trivial to automatically split the words into meaningful parts. Rule-based morphological analyzers can perform this splitting, but due to the handcrafted rules, they also suffer from an out-of-vocabulary problem. In this paper we apply a recently proposed fully automatic and rather language and vocabulary independent way to build sub-word lexica for three different agglutinative languages. We demonstrate the language portability as well by building a successful large vocabulary speech recognizer for each language and show superior recognition performance compared to the corresponding word-based reference systems.