Aplikasi Identifikasi Suara Hewan Menggunakan Metode Mel-Frequency Cepstral Coefficients (MFCC)
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Abstract
Pengenalan suara berada dibawah bidang komputasi linguistik. Hal ini mencakup identifikasi, pengakuan, dan terjemahan ucapan yang terdeteksi ke dalam teks oleh komputer. Penelitian ini menggunakan handphone dan sistem yang dirancang menggunakan suara. Tujuan utama dari penelitian ini adalah menggunakan teknik pengenalan suara untuk mendeteksi, mengidentifikasi dan menerjemahkan suara binatang. Sistem ini terdiri dari dua tahap yaitu pelatihan dan pengujian. Pelatihan melibatkan pengajaran sistem dengan membangun kamus, model akustik untuk setiap kata yang perlu dikenali oleh sistem (analisis offline). Tahap pengujian menggunakan model akustik untuk mengenali kata-kata terisolasi menggunakan algoritma klasifikasi. Aplikasi penyimpanan audio untuk mengidentifikasi berbagai suara binatang dapat dilakukan dengan lebih akurat dimasa depan.
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References
[2] Rolf Bardeli, “Similarity Search in Animal Sound Databases”, IEEE Multimedia, vol. 11, no.1, pp. 68-76, Jan 2009.
[3] Guodong Guo and Stan Z. Li, “Content-Based Audio Classification and Retrieval by Support Vector Machines”, IEEE Neural Networks, vol. 14, no. 1, Jan 2003.
[4] Michael Casey, “MPEG-7 Sound-Recognition Tools”, IEEE Trans. Circuits and systems for video technology, vol.11, no.6, June 2001.
[5] Hyoung-Gook Kim, Nicolas Moreau, and Thomas Sikora, “Audio Classification Based on MPEG-7 Spectral Basis Representations”, IEEE Tans. Circuits and systems for video technology, vol. 14, no. 5, May 2004.
[6] Michael Clausen and Frank Kurth, “A Unified Approach to Content-Based and Fault-Tolerant Music Recognition”, IEEE Trans. Multimedia, vol. 6, no. 5, Oct 2004.
[7] Panu Somervuo, Aki Härmä, and Seppo Fagerlund, “Parametric Representations of Bird Sound for Automatic Species Recognition”, IEEE Trans. Audio, Speech and Language processing, vol. 14, no. 6, Nov 2006.
[8] Deepika M and Nagalinga Rajan, “Automatic Identification of Bird Species from the Recorded Bird Song Using ART Approach”, Int. Conf. on innovations in engg., vol. 3, no. 3, Mar 2014.
[9] Yoshio Ikeda and Yohei Ishii, “Recognition of two psychological conditions of a single cow by her voice”, Journal in Computers and Electronics in Agriculture , vol. 62. no. 1, pp. 67-72 • June 2008
[10] Karthikeyan Umapathy, Sridhar Krishnan and Raveendra K. Rao, “Audio Signal Feature Extraction and Classification Using Local Discriminant Bases”, IEEE Trans. Audio, Speech and Language processing, vol. 15, no. 4, May 2007.
[11] A. D. Mane, Rashmi R. A, and S. L. Tade, “Identification & Detection System for Animals from their Vocalization”, Int. Jour. Advanced computer research, vol. 3, no. 3, Sept 2013.
[12] Khalid Saeed, “Sound and Voice Verification and Identification A Brief Review of Töeplitz Approach”,7th Conference Znalosti, pp. 22-27, 2008.
[13] Roma Bharti and Priyanka Bansal, “Real Time Speaker Recognition System using MFCC and Vector Quantization Technqiue”, Int. Jour. Computer Applications, vol. 117, no. 1, May 2015.
[14] Yu-Hsiang Bosco Chiu, Bhiksha Raj and Richard M. Stern, “Learning-Based Auditory Encoding for Robust Speech Recognition”, IEEE Trans. Audio, Speech and Language processing, vol. 0, no. 0, 2011.