Abstract
In the most recent years, numerous approaches have been accomplished in the discipline of human voice recognition for building speaker identification systems. Frequency and time domain techniques are widely used in extracting human voice features. This paper presents the most robust and most popular Mel-frequency cepstral coefficient (MFCC) technique to parameterize voices and to be used later in the voiced/unvoiced different feature extraction process methods. In addition, the direct classical techniques for human voice feature extraction purposes are used. For the purpose of the processing time consumption and to speed up the system performance for use in real-time applications, a field programming gate array (FPGA) is utilized. Its type is Altera DE2 Cyclone II.
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References
Gaikwad SK (2010) A review on speech recognition technique. Int J Comput Appl (0975–8887) 10(3)
Bachu RG, et al (2008) Separation of voiced and unvoiced using zero crossing rate and energy of the speech signal. In: American Society for Engineering Education (ASEE) zone conference proceedings
Kaur G, Singh D, Kaur G (2015) A survey on speech recognition algorithms. Int J Emerg Res Manage Technol 4(5):289–298
Shrawankar U, Thakare V (2010) Techniques for feature extraction in speech recognition system: a comparative study. Int J Comput Appl Eng Technol Sci (IJCAETS) 2(1):412–418
Poonkuzhali C, Karthiprakash R, Valarmathy S, Kalamani M (2013) An approach to feature selection algorithm based on ant colony optimization for automatic speech recognition. Int J Adv Res Electr Electron Instrum Eng 11(2) (2013)
Majeed S, Husain H, Abdulsamad S, Idbeaa T (2015) Mel Frequency Cepstral Coefficients (MFCC) feature extraction enhancement in the application of speech recognition: a comparison study. J Theor Appl Inf Technol 79(1):38–56
Rabiner LR, Juang BBH (1993) Fundamentals of speech recognition. Prentice Hall, ‎Upper Saddle River
Huang X, Acero A, Hon H-W (2001) Spoken language processing, vol 15. Prentice Hall, ‎Upper Saddle River
Von Békésy G, Wever EG (1960) Experiments in hearing, vol 8. McGraw-Hill, New York
Quatieri TF (2002) Discrete-time speech signal processing. Pearson Education, London
Xiong X (2009) Robust speech features and acoustic models for speech recognition. PhD. Thesis, Nanyang Technological University, Singapore
Rabiner LR, Schafer RW (2010) Theory and applications of digital speech processing. Pearson, London
Ephraim Y, Rahim M (1999) On second-order statistics and linear estimation of Cepstral coefficients. IEEE Trans Speech Audio Process 7:162–176
Singh P, Rani P (2014) An approach to extract features using MFCC. IOSR J Eng 4(8):21–25
Churiwala S, Hyderabad I (2017) Designing with Xilinx® FPGAs. Springer International Publishing, Cham
Bailey DG (2011) Design for embedded image processing on FPGAs. Wiley, New York
EhKan P, Allen T, QuigleySF (2011) FPGA implementation for GMM-based speaker identification. Int J Reconfig Comput 3
Chu PP (2012) Embedded SoPC design with NIOS II processor and Verilog examples. Wiley, New York
Khan ARM, Thakare AP, Gulhane SM (2010) FPGA-based design of controller for sound fetching from codec using Altera DE2 Board. Int J Sci Eng Res 1(2)
Altera DSP (2003, July) Builder–reference manual. Altera Corporation
Mathworks Homepage. https://www.mathworks.com/products/simulink.html. Last Accessed 1 Sep 2018
Nurmi J et al (eds) (2015) GALILEO positioning technology. Springer, Berlin
Tlelo-Cuautle E, de la Fraga LG, Rangel-Magdaleno J (2016) Engineering applications of FPGAs. Springer, Berlin
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Al-Shamma, O., Fadhel, M.A., Hasan, H.S. (2019). Employing FPGA Accelerator in Real-Time Speaker Identification Systems. In: Bhattacharyya, S., Pal, S., Pan, I., Das, A. (eds) Recent Trends in Signal and Image Processing. Advances in Intelligent Systems and Computing, vol 922. Springer, Singapore. https://doi.org/10.1007/978-981-13-6783-0_12
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DOI: https://doi.org/10.1007/978-981-13-6783-0_12
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