DCTX-Conformer: Dynamic context carry-over for low latency unified streaming and non-streaming Conformer ASR

arXiv:2306.08175v2 Announce Type: replace-cross
Abstract: Conformer-based end-to-end models have become ubiquitous these days and are commonly used in both streaming and non-streaming automatic speech recognition (ASR). Techniques like dual-mode and dynamic chunk training helped unify streaming and non-streaming systems. However, there remains a performance gap between streaming with a full and limited past context. To address this issue, we propose the integration of a novel dynamic contextual carry-over mechanism in a state-of-the-art (SOTA) unified ASR system. Our proposed dynamic context …

abstract arxiv asr automatic speech recognition become context cs.ai cs.lg cs.sd dynamic eess.as gap latency low low latency performance recognition speech speech recognition streaming systems training type