ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)
This paper proposes a paradigm where commonly made segmental
pronunciation errors are modeled as pair-wise confusions
between two or more phonemes in the language that is
being learnt. The method uses an ensemble of support vector
machine classifiers with time varying Mel frequency cepstral
features to distinguish between several pairs of phonemes.
These classifiers are then applied to classify the phonemes uttered
by second language learners. Instead of providing feedback
at every mispronounced phoneme, the method attempts to
provide feedback about typical mispronunciations by a certain
student, over an entire session of several utterances. Two case
studies that demonstrate how the paradigm is applied to provide
suitable feedback to two students is also described in this paper.
Index Terms. Support Vector Machines, Time Varying-MFCC, CAPT
Bibliographic reference. Ananthakrishnan, Gopal / Wik, Preben / Engwall, Olov / Abdou, Sherif (2011): "Using an ensemble of classifiers for mispronunciation feedback", In SLaTE-2011, 49-52.