- Eunah Cho, J. Niehues, Kevin Kilgour, A. Waibel. 2015. Insertion for Real-time Spoken Language Translation. Abstract: Sentence segmentation and punctuation insertion in the output of automatic recognition systems is essential for its readability as well as for the performance of subsequent applications, such as machine translation systems. While a longer context can boost the accuracy of inserted punctuation marks, it drastically increases the delay in the spoken language translation system. In this work, we investigate the impact of shorter context in punctuation insertion task on simultaneous speech translation system. We suggest a new scheme within stream decoding where the time delay consumed on punctuation prediction is avoided. Our evaluations on the English TED talks show that our suggested scheme can be used as an efficient method to punctuate recognized streams in real-time scenarios. While outperforming a conventional language model and prosody based punctuation prediction system, our model maintains a comparable performance compared to systems that require longer contexts.
