Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : speech signal

Arabic Speaker Identification System Using Multi Features

Rawia A. Mohammed; Nidaa F. Hassan; Akbas E. Ali

Engineering and Technology Journal, 2020, Volume 38, Issue 5, Pages 769-778
DOI: 10.30684/etj.v38i5A.408

The performance regarding the Speaker Identification Systems (SIS) has enhanced because of the current developments in speech processing methods, however, an improvement is still required with regard to text-independent speaker identification in the Arabic language. In spite of tremendous progress in applied technology for SIS, it is limited to English and some other languages. This paper aims to design an efficient SIS (text-independent) for the Arabic language. The proposed system uses speech signal features for speaker identification purposes, and it includes two phases: The first phase is training, in this phase a corpus of reference database is built which will serve as a reference for comparing and identifying the speaker for the second phase. The second phase is testing, which searches the identification of the speaker. In this system, the features will be extracted according to: Mel Frequency Cepstrum Coefficient (MFCC), mathematical calculations of voice frequency and voice fundamental frequency. Machine learning classification techniques: K-nearest neighbors, Sequential Minimum Optimization and Logistic Model Tree are used in the classification process. The best classification technique is a K-nearest neighbors, where it gives higher precision 94.8%.

Data Hiding in Audio File by Modulating Amplitude

Loay. A. Jorj; Hilal H. Saleh; Nidaa F.Hassan

Engineering and Technology Journal, 2010, Volume 28, Issue 5, Pages 941-952

In this paper, two methods of a steganography are introduced for hiding
secret data in audio media file (.WAV). Hiding in audio becomes a challenging
discipline, since the Human Auditory System is extremely sensitive. The first
proposed method is used to embed binary sequence with high data rate by
modulating the amplitude of WAVE file. The embedding process utilizes the
amplitude modulation of the cover signal; the manipulation of the sample depends
on its previous sample and next sample. By using this hiding method, good hiding
rate is achieved, but it is noticed that the secret data produced by this method does
not resist the modifications produced compression. The second suggested hiding
methods are oriented to embed the secret data such that it is capable of surviving
against modifications produced by compression. This method exploits some of the
features of speech signal, more especially the features of the Voiced-Unvoiced
blocks. The second proposed hiding method is used to embed secret data by
modulating the amplitude of the voiced blocks of cover audio data. Hiding rate is
not high as first method since it hiddes only in voiced segments ,so it could survive
against compression.