Indian Languages Corpus for Speech Recognition

Abstract

Robust Speech Recognition System for various languages have transcended beyond research labs to commercial products. It has been possible owing to the major developments in the area of machine learning, especially deep learning. However, development of advanced speech recognition systems could be leveraged only with the availability of specially curetted speech data. Such systems having usable quality are yet to be developed for most of the Indian languages. The present paper describes the design and development of a standard speech corpora which can be used for developing general purpose ASR systems and benchmarking them. This database has been developed for Indian languages namely Hindi, Bengali and Indian English. The corpus design incorporates important parameters such as phonetic coverage and distribution. The data was recorded by 1500 speakers in each language by male and female speakers of different age groups in varying environments. The data was recorded on a server using online recording system and transcribed using semi-automatic tools. The paper describes the corpus designing methodology, challenges faced and approach adopted to overcome them. The whole process of designing speech database has been generic enough to be used for other languages as well.