Masahiro Saiko

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This study presents the NICT automatic speech recognition (ASR) system submitted for the IWSLT 2013 ASR evaluation. We apply two types of acoustic features and three types of acoustic models to the NICT ASR system. Our system is comprised of six subsystems with different acoustic features and models. This study reports the individual results and fusion of(More)
We propose a method to adapt acoustic models for robust speech recognition in real environments using data from other languages. In real-world speech recognition systems, we can effectively adapt acoustic models using the speech data logged by the system. However, when developing a system for a new language, this step is impossible since we have no such(More)
Tone plays an important role in distinguishing lexical meaning in tonal languages, such as Mandarin and Thai. It has been revealed that tone information is helpful to improve automatic speech recognition (ASR) for these languages. In this study, we incorporate tone features from the fundamental frequency (Fo) and fundamental frequency variation (FFV) to the(More)
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