The paper presents an analysis of the voicing of the phoneme /v/ in modern spoken Macedonian. The phoneme /v/ in the standard Macedonian language is classifi ed as a fricative, but some of its characteristics separate it from the other phonemes in this group. This is due to the fact that this phoneme was once a sonorant. In a part of the Macedonian dialects this phoneme is pronounced with marked voicing to this day. This phenomenon is then refl ected in the pronunciation of standard Macedonian. Our analysis is based on a selected corpus of examples that have been spoken by speakers from various dialect origins, in order to assess the any differences in pronouncing of the phoneme /v/ when placed in different phoneme contexts in the word.
Choral singers are among intensive voice users whose excessive vocal effort puts them at risk of developing voice disorders. The aim of the work was to assess voice quality for choral singers in the choir at the Polish-Japanese Academy of Information Technology. This evaluation was carried out using the acoustic parameters from the COVAREP (A Collaborative Voice Analysis Repository For Speech Technologies) repository. A prototype of a mobile application was also prepared to allow the calculation of these parameters. The study group comprised 6 male and 19 female choir singers. The control group consisted of healthy non-singing individuals, 50 men and 39 women. Auditory perceptual assessment (using the RBH scale) as well as acoustic analysis were used to test the voice quality of all the participants. The voice quality of the female choir singers proved to be normal in comparison with the control group. The male choir singers were found to have tense voice in comparison with the controls. The parameters which proved most effective for voice evaluation were Peak Slope and Normalized Amplitude Quotient.
The paper investigates the interdependence between the perceptual identification of the vocalic quality of six isolated Polish vowels traditionally defined by the spectral envelope and the fundamental frequency F0. The stimuli used in the listening experiments were natural female and male voices, which were modified by changing the F0 values in the ±1 octave range. The results were then compared with the outcome of the experiments on fully synthetic voices. Despite the differences in the generation of the investigated stimuli and their technical quality, consistent results were obtained. They confirmed the findings that in the perceptual identification of vowels of key importance is not only the position of the formants on the F1 × F2 plane but also their relationship to F0, the connection between the formants and the harmonics and other factors. The paper presents, in quantitative terms, all possible kinds of perceptual shifts of Polish vowels from one phonetic category to another in the function of voice pitch. An additional perceptual experiment was also conducted to check a broader range of F0 changes and their impact on the identification of vowels in CVC (consonant, vowel, consonant) structures. A mismatch between the formants and the glottal tone value can lead to a change in phonetic category.
This work is complementary with Bogusław Wolniewicz’s text Elzenberg about Milosz. The circumstances surrounding the discovery of Czesław Milosz’s article Duty and Henryk Elzenberg’s polemic are portrayed here. Moreover, in the second part we have attempted to evaluate Joseph Conrad’s novel The Rover.
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.