Predictive Speech Recognition and End-of-Utterance Detection Towards Spoken Dialog Systems
Journal: arXiv (Cornell University)
Year: 2024

Effective spoken dialog systems should facilitate natural interactions with quick and rhythmic timing, mirroring human communication patterns. To reduce response times, previous efforts have focused on minimizing the latency in automatic speech recognition (ASR) to optimize system efficiency. However, this approach requires waiting for ASR to complete processing until a speaker has finished speaking, which limits the time available for natural language processing (NLP) to formulate accurate resp