F. Almasganj

Missing Feature reconstruction with Multivariate Laplace distribution (MLD) for noise robust phoneme recognition

A. Mohammadi, F. Almasganj, A. Taherkhani, 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

Pathological voice classifcation using local discriminant basis and genetic algorithm

F. Almasganj, P.T. Hosseini, M.R. Darabad, 2008, 2008 16th Mediterranean Conference on Control and Automation.

Incomplete spectrogram reconstruction with kalman filter for noise robust speech recognition

A. Mohammadi, F. Almasganj, N. Sadrieh, 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

Local Discriminant Wavelet Packet Basis for Voice Pathology Classification

F. Almasganj, P.T. Hosseini, T. Emami, 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.

Using Phoneme Segmentation in Conjunction with Missing Feature Approaches for Noise Robust Speech Recognition

A. Mohammadi, F. Almasganj, F. Naderkhani, 2007, 2007 IEEE International Symposium on Signal Processing and Information Technology.

Comparison of neural networks and support vector machines applied to optimized features extracted from patients' speech signal for classification of vocal fold inflammation

F. Almasganj, R. Behroozmand, F. Almasganj, 2005, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005..

A hybrid statistical model to generate pronunciation variants of words

F. Almasganj, B. Vazirnezhad, M. Bijankhan, 2005, 2005 International Conference on Natural Language Processing and Knowledge Engineering.

Feature bandwidth extension for Persian conversational telephone speech recognition

F. Almasganj, Y. Shekofteh, J. Kabudian, 2012, 20th Iranian Conference on Electrical Engineering (ICEE2012).

Study of VTLN method to recognize common speech disorders in speech therapy of Persian children

F. Almasganj, F. Towhidkhah, S. Azizi, 2012, 2012 19th Iranian Conference of Biomedical Engineering (ICBME).

Detecting simulated sprained ankle plantar pressure pattern using artificial neural network

F. Almasganj, S. Najarian, S. H. Farkoush, 2009, 2009 IEEE Symposium on Industrial Electronics & Applications.