The purpose of this paper is to address the challenges and describe step-by-step solutions faced when developing an automatic speech recognition system in multilingual societies. We give a brief statistical analysis of the data that have been harvested from the internet. The harvesting process operates in a multilingual environment where code-switching is the norm. We specifically focus our attention on the challenge of number normalization, pronunciation and the variations associated with it. We then develop various systems to illustrate the effects of different approaches to modelling the pronunciation of numbers.
Reference:
Molapo, R and Barnard, E. 2014. Number pronunciation in a multilingual environment and implications for an ASR system. Pattern Recognition Association of South Africa (PRASA), Cape Town, South Africa, 27 - 28 November 2014, pp 138-141
Molapo, R., & Barnard, E. (2014). Number pronunciation in a multilingual environment and implications for an ASR system. Pattern Recognition Association of South Africa. http://hdl.handle.net/10204/7902
Molapo, R, and E Barnard. "Number pronunciation in a multilingual environment and implications for an ASR system." (2014): http://hdl.handle.net/10204/7902
Molapo R, Barnard E, Number pronunciation in a multilingual environment and implications for an ASR system; Pattern Recognition Association of South Africa; 2014. http://hdl.handle.net/10204/7902 .