Abstract
This paper proposes a genetic-fuzzy system for speech recognition. In addition to pre-processing, with mel-cepstral coefficients, the Discrete Cosine Transform (DCT) is used to generate a two-dimensional time matrix for each pattern to be recognized. A genetic algorithm is used to optimize a Mamdani fuzzy inference system in order to obtain the best model for final recognition. The speech recognition system used in this paper was named Hybrid Method Genetic-Fuzzy Inference System for Speech Recognition (HMFE).
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Silva, W., Serra, G. (2012). An Intelligent System Based on Discrete Cosine Transform for Speech Recognition. In: Pavón, J., Duque-Méndez, N.D., Fuentes-Fernández, R. (eds) Advances in Artificial Intelligence – IBERAMIA 2012. IBERAMIA 2012. Lecture Notes in Computer Science(), vol 7637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34654-5_33
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DOI: https://doi.org/10.1007/978-3-642-34654-5_33
Publisher Name: Springer, Berlin, Heidelberg
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