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Spoken language processing poses to be a challenging task in multilingual and mixlingual scenario in linguistically diverse regions like Indian subcontinent. Common articulatory based framework is explored for the representation of phonemes of different languages. This framework is designed to handle typical features like aspirated plosives, nasalized vowels, combined letters, unvoiced retroflex plosive...
This work presents a novel technique to represent Indian phonemes using English articulatory motivated posteriorgrams. Changes are done in articulatory posteriorgrams trained in English language to bring out minute details which are significant in multilingual scenario. With these enhancements, we show that articulatory posteriorgrams can give comparable or slightly better performance than the state-of-the-art...
This paper addresses the problem of Query-by-Example Spoken Term Detection (QbE-STD). Posteriorgrams have been widely used in the research on QbE-STD. Features based on articulatory classes are known to be robust to phonemic variations. The articulatory features like voicing and place of articulation are the main distinguishing features among some plosives and fricatives. These properties inspire...
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