5 research outputs found
Ear–voice span and pauses in intra- and interlingual respeaking: An exploratory study into temporal aspects of the respeaking process
Respeaking involves producing subtitles in real time to make live television programs accessible to deaf and hard of hearing viewers. In this study we investigated how the type of material to be respoken affects temporal aspects of respeaking, such as ear–voice span and pauses. Given the similarities between respeaking and interpreting (time constraints) and between interlingual respeaking and translation (interlingual processing), we also tested whether previous interpreting and translation experience leads to a smaller delay or lesser cognitive load in respeaking, as manifested by a smaller number of pauses. We tested 22 interpreters, 23 translators, and a control group of 12 bilingual controls, who performed interlingual (English to Polish) and intralingual (Polish to Polish) respeaking of five video clips with different characteristics (speech rate, number of speakers, and scriptedness). Interlingual respeaking was found to be more challenging than the intralingual one. The temporal aspects of respeaking were affected by clip type (especially in interpreters). We found no clear interpreter or translator advantage over the bilingual controls across the respeaking tasks. However, interlingual respeaking turned out to be too difficult for many bilinguals to perform at all. To the best of our knowledge, this is the first study to examine temporal aspects of respeaking as modulated by the type of materials and previous interpreting/translation experience. The results develop our understanding of temporal aspects of respeaking and are directly applicable to respeaker training
System for Automatic Transcription of Sessions of the Polish Senate
This paper describes research behind a Large-Vocabulary Continuous Speech Recognition (LVCSR)
system for the transcription of Senate speeches for the Polish language. The system utilizes several
components: a phonetic transcription system, language and acoustic model training systems, a Voice
Activity Detector (VAD), a LVCSR decoder, and a subtitle generator and presentation system. Some of
the modules relied on already available tools and some had to be made from the beginning but the authors
ensured that they used the most advanced techniques they had available at the time. Finally, several
experiments were performed to compare the performance of both more modern and more conventional
technologies