Ahmed Ali

Ahmed Ali
University of Technology, Iraq · Department of Electro-Mechanical Engineering

Doctor of Engineering

About

7
Publications
1,907
Reads
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82
Citations
Citations since 2017
6 Research Items
82 Citations
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Introduction
Dr. Ahmed Kamil Hasan AL-ALI is a lecturer at the Electromechanical Department, University of Technology, Baghdad-Iraq. He obtained his BSc in Electrical Engineering in 2001 and MSc in Communication and Electronics from Al-Mustansiriyah University in 2005. He was awarded PhD degree in Electrical Engineering/ Communication in 2019 from the Queensland University of Technology, Australia. Ahmed is an Associate fellow of higher education Academy in 2018.
Skills and Expertise
Electrical & Electronics Engineering
Signal Processing
Independent Component Analysis
Speech Enhancement
Speaker Recognition
Forensic Speaker Verification
MATLAB
Wavelet Transform
Discrete Wavelet Transform

Publications

Publications (7)
Fig. 1 Configuration of sources and microphones in instantaneous ICA...
Fig. 2 Position of suspect and microphone in a room. Microphone and...
Fig. 3 Flowchart of the proposed approach of forensic speaker...
Fig. 4 A block diagram of the MFCC feature extraction.
+14 Fig. 5 Block diagram of the DWT.
Enhanced Forensic Speaker Verification Performance Using the ICA-EBM Algorithm Under Noisy and Reverberant Environments
Article
Full-text available
  • Dec 2021
Forensic speaker verification performance reduces significantly under high levels of noise and reverberation. Multiple channel speech enhancement algorithms, such as independent component analysis by entropy bound minimization (ICA-EBM), can be used to improve noisy forensic speaker verification performance. Although the ICA-EBM was used in previou...
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Figure 2.1: Text-independent speaker verification system.
Figure 2.7: Length-normalized GPLDA based speaker verification system.
Figure 2.8: An example of DET plot.
Figure 3.2: Position of speech and noise signals to the microphones.
+16 Figure 3.8: Design of a multiple microphones adverse framework based on...
FORENSIC SPEAKER RECOGNITION UNDER ADVERSE CONDITIONS
Thesis
Full-text available
  • Jul 2019
The performance of forensic speaker recognition systems degrades significantly in the presence of environmental noise and reverberant conditions. This research developed new techniques to improve forensic speaker recognition performance under these conditions using fusion feature extraction techniques and speech enhancement based on the independent...
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FIGURE 1. Diagram of the room. 
FIGURE 2. A block diagram of extracting the MFCC features. 
FIGURE 5. Effect of the decomposition levels on the performance of...
FIGURE 6. Effect of the utterance length on the performance of fusion...
+12 FIGURE 7. Average reduction in EER for fusion feature-warped DWT-MFCC...
Enhanced Forensic Speaker Verification Using A Combination of DWT and MFCC Feature Warping in the Presence of Noise and Reverberation Conditions
Article
Full-text available
  • Dec 2017
Environmental noise and reverberation conditions severely degrade the performance of forensic speaker verification. Robust feature extraction plays an important role in improving forensic speaker verification performance. This paper investigates the effectiveness of combining features, mel frequency cepstral coefficients (MFCCs), and MFCC extracted...
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Figure 1: Comparison of average SNR enhancement when street noise is...
Figure 3: Comparison of average SNR enhancement when car noise is added...
comparison of speech enhancement algorithms for forensic applications
Conference Paper
Full-text available
  • Jan 2016
Speech enhancement algorithms play an essential role in forensic applications, and enhanced speech signals can be used in court as evidence in criminal cases. This paper compares the performance of single channel (spectral subtraction and level dependent wavelet threshold techniques) and multiple channel (independent component analysis or ICA) spee...
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Projects

Projects (2)
Enhanced Forensic speaker verification using a combination of DWT and MFCC feature warping in the presence of noise and reverberation conditions
Project
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Advances in Biometrics
Archived project
The objectives are : * use high resolution, non-contact images of the full hand for biometric identification * robust feature extraction for speaker verification in forensic applications (2 PhD students currently externally supervised)
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