Massively Multilingual Adversarial Speech Recognition

NAACL 2019 Oliver AdamsMatthew WiesnerShinji WatanabeDavid Yarowsky

We report on adaptation of multilingual end-to-end speech recognition models trained on as many as 100 languages. Our findings shed light on the relative importance of similarity between the target and pretraining languages along the dimensions of phonetics, phonology, language family, geographical location, and orthography... (read more)

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