Low-Latency Sequence-to-Sequence Speech Recognition and Translation by Partial Hypothesis Selection
Table 3: Incremental speech translation performance on How2 300h English-Portuguese.
['[BOLD] Strategies', '[BOLD] BLEU', '[BOLD] METEOR', 'Δ [BOLD]  latency (sec.)']
We use BLEU [papineni-etal-2002-bleu, post-2018-call] and METEOR [banerjee-lavie-2005-meteor] as quality metrics. The results here agree with the previous findings on ASR. In general, by selectively taking prefixes of chunk-level hypotheses, we can largely reduce latency by sacrificing some output quality. More importantly, the local agreement selection strategy remains to achieve the most efficient quality-latency trade-off. It scores similarly to the hold-4 strategy in term of the quality metrics but has 0.2 second less latency. Compared to the offline system, we see an 84% relative reduction in latency with a 5% relative loss in BLEU and METEOR.