Phone set generation based on acoustic and contextual analysis for multilingual speech recognition

This study presents a novel approach to generating phone units generation for the recognition of multilingual speech. Acoustic and contextual analysis is performed to characterize multilingual phonetic units for phone set generation. A confusion matrix combining acoustic and contextual similarities between every two phonetic units is constructed for phonetic unit clustering. Acoustic likelihood and hyperspace analog to language (HAL) model are adopted for acoustic similarity and contextual similarity estimation of phone models, respectively. Experiments show that the generated phone set provides a compact and robust set that considers acoustic and contextual information for multilingual speech recognition.