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We evaluate different architectures to recognize multilingual speech for real-time mobile applications. In particular, we show that combining the results of several recognizers greatly outperforms other solutions such as training a single large multilingual system or using an explicit language identification system to select the appropriate recognizer. Experiments are conducted on a trilingual English-French-Mandarin...
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