A first speech recognition system for Mandarin-English code-switch conversational speech

• Main Authors: Vu, Ngoc Thang, Lyu, Dau-Cheng, Weiner, Jochen, Telaar, Dominic, Schlippe, Tim, Blaicher, Fabian, Chng, Eng Siong, Schultz, Tanja, Li, Haizhou
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/98522; http://hdl.handle.net/10220/13411
• Institution: Nanyang Technological University

This paper presents first steps toward a large vocabulary continuous speech recognition system (LVCSR) for conversational Mandarin-English code-switching (CS) speech. We applied state-of-the-art techniques such as speaker adaptive and discriminative training to build the first baseline system on the SEAME corpus [1] (South East Asia Mandarin-English). For acoustic modeling, we applied different phone merging approaches based on the International Phonetic Alphabet (IPA) and Bhattacharyya distance in combination with discriminative training to improve accuracy. On language model level, we investigated statistical machine translation (SMT) - based text generation approaches for building code-switching language models. Furthermore, we integrated the provided information from a language identification system (LID) into the decoding process by using a multi-stream approach. Our best 2-pass system achieves a Mixed Error Rate (MER) of 36.6% on the SEAME development set.