Abstract

As automatic speech recognition-based applications become increasingly common in a wide variety of market segments, thereis a growing need to support more languages. However, for many languages, the language resources needed to train speechrecognition engines are either limited or completely non-existent, and the process of acquiring or constructing new languageresources is both long and costly. This paper suggests a methodology that enables Phonetic Search Keyword Spotting to beimplemented in a large speech database of any given under-resourced language using cross-language phoneme mappings toanother language. The phoneme mapping enables a speech recognition engine from a sufficiently resourced and well-trainedsource language to be used for phoneme recognition in the new target language. The keyword search is then performed overa lattice of target language phonemes. Three cross-language phoneme mapping techniques are examined: knowledge-based,data-driven and phoneme recognition performance-based. The results suggest that Phonetic Search Keyword Spotting basedon the cross-language phoneme mapping approach proposed herein can serve as a quick initial solution for validating keywordspotting applications in new, under-resourced languages.

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