A Survey on Signal Processing Based Pathological Voice Detection Techniques

Text-dependent pathological voice detection

While global characteristics of the speaker’s source and spectral features have been successfully employed in pathological voice detection, the underlying text has largely been ignored. In this work, we focus on experiments that exploit the text stimulus that is read by the subject. Features derived from text include the mean cepstral distortion of the subject from an average intelligible speak...

Voice Disorder Detection Based on Automatic Speaker Identification Techniques

In this paper, we investigate the proprieties of automatic speaker identification (ASI) to develop a system for voice pathologies detection, where the models do not correspond to different speakers but it corresponds to classes of patients who share the same diagnostic. One essential part in this topic is the database (described later), the samples voices (healthy and pathological) are chosen f...

P81: Detection of Epileptic Seizures Using EEG Signal Processing

Epilepsy is the most common brain diseases that cause many problems in the daily life of the patient. In most attempts to automatic detection, the attack used an EEG. In this paper, The complete data set consists of five sets recorded from normal and epileptic patients. Each set containing 100 single-channel EEG segments. Here we used first and last sets (A and E). Set A consisted of segments r...

Principal component analysis for HMM-based pathological voice detection

A Survey on IDS Alerts Processing Techniques

When an attacker tries to penetrate the network, there are many defensive systems, including intrusion detection systems (IDSs). Most IDSs are capable of detecting many attacks, but can not provide a clear idea to the analyst because of the huge number of false alerts generated by these systems. This weakness in the IDS has led to the emergence of many methods in which to deal with these alerts...