Title :
English to Japanese spoken language translation system for classroom lectures
Author :
Ferdiansyah, Veri ; Nakagawa, Sachiko
Author_Institution :
Dept. of Comput. Sci. & Eng., Toyohashi Univ. of Technol., Toyohashi, Japan
Abstract :
This paper presents our attempt to create English automatic speech recognition (ASR) and English to Japanese statistical machine translation system (SMT). We used MIT OpenCourseWare lectures as our test lecture corpus. Wall Street Journal (WSJ) corpus adapted with MIT OpenCourseWare lectures was used as our acoustic model. MIT OpenCourseWare lecture transcriptions were utilized to create our language model. As for the parallel corpus, we used TED Talks and Japanese-English News Article Alignment Data (JENAAD). Our proposed ASR system can achieve 32.1% 0word error rate (WER) and our SMT system can achieve 10.95 BLEU.
Keywords :
courseware; language translation; speech recognition; ASR system; English automatic speech recognition; English-to-Japanese statistical machine translation system; JENAAD; JapaneseEnglish News Article Alignment Data; MIT OpenCourseWare lectures; SMT system; TED Talks; WER; WSJ corpus; Wall Street Journal corpus; acoustic model; classroom lectures; lecture transcriptions; word error rate; Acoustics; Adaptation models; Data models; Hidden Markov models; Informatics; Speech; Speech recognition; MIT OCW; automatic speech recognition; classroom lectures; machine translation;
Conference_Titel :
Advanced Informatics: Concept, Theory and Application (ICAICTA), 2014 International Conference of
Conference_Location :
Bandung
Print_ISBN :
978-1-4799-6984-5
DOI :
10.1109/ICAICTA.2014.7005911
