Application of support vector machines and two dimensional discrete cosine transform in speech automatic recognition
Gracieth C. Batista, Washington Luis Santos Silva · 2015
This paper proposes the implementation of a Support Vector Machine (SVM) for automatic recognition of numerical speech commands. Besides the pre-processing of the speech signal with mel-ceptral coefficients, is used to Discrete Cosine Transform (DCT) to generate a two-dimensional matrix used as input to SVM algorithm for generating the pattern of words to be recognized. The Support Vector Machines represent a new approach to pattern classification. SVM is used to recognize speech patterns from the mean and variance of the speech signal input through the two-dimensional array aforementioned, the algorithm trains and tests those data showing the best response. Finally shows the experimental results in speech recognition applied to Brazilian Portuguese language process.