Efficient Punctuation Restoration via Weighted Lookahead Scoring Method for Streaming ASR Systems

This paper introduces a non-autoregressive scoring method for efficient punctuation restoration in streaming Automatic Speech Recognition (ASR) systems. It compares punctuation insertion hypotheses against a no-insertion baseline using a bounded K-subword-token lookahead, outperforming existing prompt-based methods.