Abstract:Speech systems are sensitive to accent variations. This is especially challenging in the Indian context, with an abundance of languages but a dearth of linguistic studies characterising pronunciation variations. The growing number of L2 English speakers in India reinforces the need to study accents and L1-L2 interactions. We investigate the accents of Indian English (IE) speakers and report in detail our observations, both specific and common to all regions. In particular, we observe the phonemic variations and phonotactics occurring in the speakers' native languages and apply this to their English pronunciations. We demonstrate the influence of 18 Indian languages on IE by comparing the native language pronunciations with IE pronunciations obtained jointly from existing literature studies and phonetically annotated speech of 80 speakers. Consequently, we are able to validate the intuitions of Indian language influences on IE pronunciations by justifying pronunciation rules from the perspective of Indian language phonology. We obtain a comprehensive description in terms of universal and region-specific characteristics of IE, which facilitates accent conversion and adaptation of existing ASR and TTS systems to different Indian accents.
Abstract:In contrast to British or American English, labeled pronunciation data on the phonetic level is scarce for Indian English (IE). This has made it challenging to study pronunciations of Indian English. Moreover, IE has many varieties, resulting from various native language influences on L2 English. Indian English has been studied in the past, by a few linguistic works. They report phonetic rules for such characterisation, however, the extent to which they can be applied to a diverse large-scale Indian pronunciation data remains under-examined. We consider a corpus, IndicTIMIT, which is rich in the diversity of IE varieties and is curated in a nativity balanced manner. It contains data from 80 speakers corresponding to various regions of India. We present an approach to validate the phonetic rules of IE along with reporting unexplored rules derived using a data-driven manner, on this corpus. We also provide quantitative information regarding which rules are more prominently observed than the others, attributing to their relevance in IE accordingly.