Utilizing Lipreading in Large Vocabulary Continuous Speech Recognition

摘要

Vast majority of current research in the area of audiovisual speech recognition via lipreading from frontal face videos focuses on simple cases such as isolated phrase recognition or structured speech, where the vocabulary is limited to several tens of units. In this paper, we diverge from these traditional applications and investigate the effect of incorporating the visual information in the task of continuous speech recognition with vocabulary size ranging from several hundred to half a million words. To this end, we evaluate various visual speech parame-trizations, both existing and novel, that are designed to capture different kind of information in the video signal. The experiments are conducted on a moderate sized dataset of 54 speakers, each uttering 100 sentences in Czech language. We show that even for large vocabularies the visual signal contains enough information to improve the word accuracy up to 15% relatively to the acoustic-only recognition.