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Code-switching or mixing is the use of multiple languages in a single utterance or conversation. Borrowing occurs when a word from a foreign language becomes part of the vocabulary of a language. In multilingual societies, switching/mixing and borrowing are not always clearly distinguishable. Due to this, transcription of code-switched and borrowed words is often not standardized, and leads to the presence of homophones in the training data. In this work, we automatically identify and disambiguate homophones in code-switched data to improve recognition of code-switched speech. We use a WX-based common pronunciation scheme for both languages being mixed and unify the homophones during training, which results in a lower word error rate for systems built using this data.

Added on May 9, 2019

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  • Contributed by : Individual
  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : Brij Mohan Lal Srivastava, Sunayana Sitaram
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