Sentence segmentation and punctuation recovery for spoken language translation

Sentence segmentation and punctuation recovery are critical components for effective spoken language translation (SLT). In this paper we describe our recent work on sentence segmentation and punctuation recovery for three different language pairs, namely for English-to-Spanish, Arabic-to-English and Chinese-to-English. We show that the proposed approach works equally well in these very different language pairs. Furthermore, we introduce two features computed from the translation beam-search lattice that indicate if phrasal and target language model context is jeopardized when segmenting at a given word boundary. These features enable us to introduce short intra-sentence segments without degrading translation performance.