A Mandarin E-Learning System Based on Speech Recognition and Evaluation
This paper establishes a speaker-independent pronunciation recognition and assessment system under the background of a Mandarin e-learning system framework. The recognition part is based on Hidden Markov Models (HMM) and improved in the aspect of acoustic and tone model. Making use of the recognition and detection results and corresponding parametric scorings, the machine scoring is performed to evaluate the quality of pronunciation its correlation with expert score are discussed. Through integrating recognition and assessment system with Web 2.0, we ultimately establish an open, shared and growing-up virtual Mandarin learning community, where all of learners, viewers, professors, without any restrictions on time and places, can express their perspective about how to advance Mandarin learning freely. (C) 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 19: 651-659, 2011; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.20349
speech recognition web 2.0 mandarin learning community pronunciation evaluation tone recognition