Survey: Exploring Disfluencies for Speech To Text Machine Translation

Spoken language is different from the written language in its style and structure. Disfluencies that appear in transcriptions from speech recognition systems generally hamper the performance of downstream NLP tasks. Thus, a disfluency correction system that converts disfluent to fluent text is of great value. This survey paper talks about disfluencies present in speech and its transcriptions. Later, we describe methodologies to correct disfluencies present in the transcriptions of a spoken utterance via various approaches viz, a) style transfer for disfluency correction b) transfer learning and language model pretraining. We observe that disfluency inherent speech phenomenon and its correction is crucial for downstream NLP tasks.