Sådhanå (2018) 43:53 © Indian Academy of Sciences https://doi.org/10.1007/s12046-018-0841-ySadhana(0123456789().,-volV)FT3](0123456789().,-volV) Spoken Indian language identification: a review of features and databases BAKSHI AARTI1,* and SUNIL KUMAR KOPPARAPU2 1 Department of Electronics and Communication, UMIT, SNDT University, Mumbai 400020, India 2 TCS Innovation Labs - Mumbai, TATA Consultancy Services, Yantra Park, Thane 400606, India e-mail:
[email protected];
[email protected] MS received 14 October 2015; revised 10 April 2017; accepted 19 February 2018; published online 12 April 2018 Abstract. Spoken language is one of the distinctive characteristics of the human race. Spoken language processing is a branch of computer science that plays an important role in human–computer interaction (HCI), which has made remarkable advancement in the last two decades. This paper reviews and summarizes the acoustic, phonetic and prosody features that have been used for spoken language identification specifically for Indian languages. In addition, we also review the speech databases, which are already available for Indian languages and can be used for the purposes of spoken language identification. Keywords. SLID; phonetic; characteristics; features. 1. Introduction and phonotactics associated with speech are widely used in automatic SLID task [1]. Spoken language is the most natural mode of communi- Speech features are a compact representation and/or cation in today’s world, especially given the advances that parameterization of the raw acoustic speech signal. have happened in the area of automatic speech recognition Acoustic features extracted from the speech signal have (ASR). However, to achieve good ASR performance in been widely used for SLID.