Abstract
In this chapter, a technique is proposed to remove the CVC-type word limitation observed in case of spoken word recognition model described in Chap. 7. This technique is based on a phoneme count determination block based on K-means clustering (KMC) of speech data. Sections 8.2 and 8.3 of this chapter provides detail description of a K-mean algorithm-based technique to provide prior knowledge about the possible number of phonemes in a word. Experimental work, related to the proposed technique, is discussed in Sect. 8.4. Section 8.5 concludes the description.
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References
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Sarma, M., Sarma, K.K. (2014). Application of Clustering Techniques to Generate a Priori Knowledge for Spoken Word Recognition. In: Phoneme-Based Speech Segmentation using Hybrid Soft Computing Framework. Studies in Computational Intelligence, vol 550. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1862-3_8
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DOI: https://doi.org/10.1007/978-81-322-1862-3_8
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