| Paper title: |
Speech Recognition |
| Published in: | Issue 2, (Vol. 3) / 2009 |
| Publishing date: | 2009-10-20 |
| Pages: | 54-59 |
| Author(s): | Morariu Adrian |
| Abstract. | This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients) by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients. |
| Keywords: | Voice Recognition, Hamming Window, Fourier Transform, Magnitude Spectrum, The Cepstral Coefficients |
| References: | 1. Stefan-Gheorghe Pentiuc, Recunoasterea Formelor, Metode, Programe si Aplicatii, Editura Universitatii Stefan Cel Mare Suceava 1996 2. Lawrence Rabiner and Biing-Hwang Juang, Fundamentals of Speech Recognition 3. Oran Brigham, Fast Fourier Transform And Its Applications 4. http://en.wikipedia.org/wiki/Audio_signal_processing 5. http://en.wikipedia.org/wiki/Fast_Fourier_transform 6. http://en.wikipedia.org/wiki/K-means_clustering |
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