Karya
Judul/Title Wavelet Based Feature Extraction for the Indonesian CV Syllables Sound
Penulis/Author DOMY KRISTOMO (1) ; Prof. Dr. Ir. Risanuri Hidayat, M.Sc., IPM. (2); Dr. Indah Soesanti, S.T., M.T. (3)
Tanggal/Date 2018
Kata Kunci/Keyword
Abstrak/Abstract This paper proposes the combined methods of Wavelet Transform (WT) and Euclidean Distance (ED) to estimate the expected value of the possibly feature vector of Indonesian syllables. This research aims to find the best properties in effectiveness and efficiency on performing feature extraction of each syllable sound to be applied in the speech recognition systems. This proposed approach which is the state-of-the-art of the previous study consist of three main phase. In the first phase, the speech signal is segmented and normalized. In the second phase, the signal is transformed into frequency domain by using the WT. In the third phase, to estimate the expected feature vector, the ED algorithm is used. Th e result shows the list of features of each syllables can be used for the next research, and some recommendations on the most effective and efficient WT to be used in performing syllable sound recognition
Rumpun Ilmu Teknik Elektro
Bahasa Asli/Original Language Bahasa Indonesia
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
110 Wavelet Based Feature Extraction for the Indonesian CV Syllables Sound.pdf[PAK] Full Dokumen
2Similarity Wavelet Based Feature Extraction for the Indonesian CV Syllables Sound.pdf[PAK] Cek Similarity
3Wavelet based feature extraction for the Indonesian CV syllables sound.pdf[PAK] Full Dokumen
4Wavelet Based Feature Extraction for the Indonesian CV Syllables Sound.pdf[PAK] Cek Similarity
5Wavelet based feature extraction for the Indonesian CV syllables sound.pdf[PAK] Full Dokumen