Abstract
In this paper we present a new approach to the problem of isolated vowel recognition in real-time. Language learning and speech therapy are examples of application areas that require real-time biofeedback of acoustic features. As the performance of known approaches usually drops for child speakers, we evaluated different alternatives of feature extraction and pattern recognition techniques, including PCA, LDA, ANN and Bayesian classification. In addition, we studied the explicit inclusion of pitch as a main parameter in both simulation and the real-time feature extraction process. Best results were obtained with our dataset when MFCCs are mapped, using LDA, to a 4-dimensional subspace that is followed by Bayesian classification. An interactive game was designed that implements the selected real-time vowel recognition technique.
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Carvalho, M., Ferreira, A. (2008). Real-Time Recognition of Isolated Vowels. In: André, E., Dybkjær, L., Minker, W., Neumann, H., Pieraccini, R., Weber, M. (eds) Perception in Multimodal Dialogue Systems. PIT 2008. Lecture Notes in Computer Science(), vol 5078. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69369-7_18
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DOI: https://doi.org/10.1007/978-3-540-69369-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69368-0
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