Classification of CV transitions in continuous speech using neural network models

Presents an approach to classification of place of articulation (POA) of stop consonants in continuous speech. As the clues for POA are dependent on the formant transitions between a consonant and its following vowel, the authors propose to classify the CV transition rather than just the POA. They also propose pitch region analysis based signal processing methods to extract parameters suitable for classification of CV transitions. They present the results of their studies on classification using the multilayer perceptron model and compare the performance for different parametric representations