The human voice is one of the basic means of communication, thanks to which one also can easily convey the emotional state. This paper presents experiments on emotion recognition in human speech based on the fundamental frequency. AGH Emotional Speech Corpus was used. This database consists of audio samples of seven emotions acted by 12 different speakers (6 female and 6 male). We explored phrases of all the emotions – all together and in various combinations. Fast Fourier Transformation and magnitude spectrum analysis were applied to extract the fundamental tone out of the speech audio samples. After extraction of several statistical features of the fundamental frequency, we studied if they carry information on the emotional state of the speaker applying different AI methods. Analysis of the outcome data was conducted with classifiers: K-Nearest Neighbours with local induction, Random Forest, Bagging, JRip, and Random Subspace Method from algorithms collection for data mining WEKA. The results prove that the fundamental frequency is a prospective choice for further experiments.

The goal of this article is to present and compare recent approaches which use speech and voice analysis as biomarkers for screening tests and monitoring of some diseases. The article takes into account metabolic, respiratory, cardiovascular, endocrine, and nervous system disorders. A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. Information was extracted from each paper in order to compare various aspects of datasets, speech parameters, methods of applied analysis and obtained results. 110 research papers were reviewed and 47 databases were summarized. Speech analysis is a promising method for early diagnosis of certain disorders. Advanced computer voice analysis with machine learning algorithms combined with the widespread availability of smartphones allows diagnostic analysis to be conducted during the patient’s visit to the doctor or at the patient’s home during a telephone conversation. Speech analysis is a simple, low-cost, non-invasive and easy-toprovide method of medical diagnosis. These are remarkable advantages, but there are also disadvantages. The effectiveness of disease diagnoses varies from 65% up to 99%. For that reason it should be treated as a medical screening test and should be an indication of the need for classic medical tests.