INTERSPEECH 2007
8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Punctuating Confusion Networks for Speech Translation

Roldano Cattoni, Nicola Bertoldi, Marcello Federico

FBK-irst, Italy

Translating from confusion networks (CNs) has been proven to be more effective than translating from single best hypotheses. Moreover, it is widely accepted that the availability of good punctuation marks in the input can improve translation quality. At present, no ASR systems can generate punctuation marks in the word graphs, therefore CNs miss punctuation. In this paper we investigate the problem of adding punctuation marks into confusion networks. We investigate different punctuation strategies and show that the use of multiple hypotheses improves translation quality in a large-vocabulary speech translation task.

Full Paper

Bibliographic reference.  Cattoni, Roldano / Bertoldi, Nicola / Federico, Marcello (2007): "Punctuating confusion networks for speech translation", In INTERSPEECH-2007, 2453-2456.