Uma, S and Sridhar, V and Krishna, G (1992) Time-Normalization Techniques for Speaker-Independent Isolated Word Recognition. In: 11th IAPR International Conference on Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, 30th August-3rd September, Hague, pp. 537-540.
In this paper, we investigate various timenormalization techniques that are useful in the context of speaker-independent isolated word recognition. At the lowest level, we make use of LPC coefficients as the features to be nomalized. We discuss the various methods by which we can normalize these features. To begin with, we arrive at a typical number of frames associated with a word. Then, we normalize all the training and test data to this number of frames. Initial results bring out the point that normalization techniques help in reducing the number of patterns with which the unknown has to be compared.
|Item Type:||Conference Paper|
|Additional Information:||Copyright 1992 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||25 Aug 2008|
|Last Modified:||19 Sep 2010 04:28|
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