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Automatic speech recognition systems (ASR) have achieved considerable progress in real applications because of skilled design of the architecture with advanced techniques and algorithms. However, how to design a system efficiently integrating these various techniques to obtain advanced performance is still a challenging task. In this paper, we introduced an ensemble model combination and adaptation...
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 convolutional neural network (CNN), a state-of-the-art...
We propose a new multi-lingual unsupervised acoustic model (AM) training method for low-resourced languages under mismatch conditions. In those languages, there is very limited or no transcribed speech. Thus, unsupervised acoustic modeling using AMs of different languages (not low-resourced languages) has been proposed. The conventional method has shown to be effective for similar acoustic conditions,...
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