Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training

@article{Gonen2018LanguageMF,
  title={Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training},
  author={Hila Gonen and Yoav Goldberg},
  journal={ArXiv},
  year={2018},
  volume={abs/1810.11895}
}
We focus on the problem of language modeling for code-switched language, in the context of automatic speech recognition (ASR). Language modeling for code-switched language is challenging for (at least) three reasons: (1) lack of available large-scale code-switched data for training; (2) lack of a replicable evaluation setup that is ASR directed yet isolates language modeling performance from the other intricacies of the ASR system; and (3) the reliance on generative modeling. We tackle these… CONTINUE READING
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