Phonetic unit selection for cross-lingual query-by-example spoken term detection

Abstract

Cross-lingual query-by-example spoken term detection (QbE STD) has caught the attention of speech researchers, as it makes it possible to develop systems for low-resource languages, in which the available amount of labelled data makes the training of automatic speech recognition approaches prohibitive. The use of phonetic posteriorgrams for speech representation combined with dynamic time warping search is a widely used approach for this task, but little attention has been focused in the suitability of a set of phonetic units to represent speech information spoken in a different language. This paper proposes a technique for estimating the relevance of phonetic units aiming at selecting the most suitable ones for a given target language. Experiments in a Spanish database using phoneme posteriorgrams in Czech, English, Hungarian and Russian proved the validity of the proposed method, as QbE STD performance was enhanced by reducing the set of phonetic units.