Code-switching is a phenomenon in linguistics which refers to the use of two or more languages, especially within the same discourse. This phenomenon has been observed in many multilingual communities across the globe. In the recent past, there have been increasing demand for automatic speech recognition (ASR) systems to deal with code-switching. However, for training such systems, very limited code-switching resources are available as yet. Thus, the development of code-switching resources is highly desirable. In this work, we describe the collection of a Hinglish (Hindi-English) code-switching database at the Indian Institute of Technology Guwahati (IITG) which is referred to as the IITG-HingCoS corpus. This corpus consists of code-switching text data having 25,988 sentences with a total of 0.58 million words. In addition to that, the corpus also contains 25 h of matching speech data corresponding to 9251 code-switching sentences covering a vocabulary of 6542 words. This paper elaborates the sources and the protocol used for collecting the corpus. The baseline experimental results on the collected corpus for language modeling and ASR tasks are also presented.
Link to paper: https://www.sciencedirect.com/science/article/abs/pii/S0167639318304217
Link to paper: https://www.sciencedirect.com/science/article/abs/pii/S0167639318304217