Automatic Detection of Code-switching Style from Acoustics
SaiKrishna Rallabandi, Sunayana Sitaram, Alan W. Black · 2018
Multilingual speakers switch between languages displaying inter sentential, intra sentential, and congruent lexicalization based transitions.While monolingual ASR systems may be capable of recognizing a few words from a foreign language, they are usually not robust enough to handle these varied styles of code-switching.There is also a lack of large code-switched speech corpora capturing all these styles making it difficult to build code-switched speech recognition systems.We hypothesize that it may be useful for an ASR system to be able to first detect the switching style of a particular utterance from acoustics, and then use specialized language models or other adaptation techniques for decoding the speech.In this paper, we look at the first problem of detecting code-switching style from acoustics.We classify code-switched Spanish-English and Hindi-English corpora using two metrics and show that features extracted from acoustics alone can distinguish between different kinds of codeswitching in these language pairs.