Distinctive feature based SVM discriminant features for improvements to phone recognition on telephone band speech
Support vector machines (SVM’s) can be trained to classify manner transitions between phones and to identify the place of articulation of any given phone with high accuracy. The discriminant outputs of these SVM’s can be used as input features for a standard ASR system. There is a signiﬁcant improvement in correctness and accuracy using these SVM discriminant features when compared to an MFCC based recognizer of equal parameters.