This paper presents the results of measurements of the sound absorption coefficient of auditorium seats carried out in the laboratory using two methods. In the first one, small blocks of seats in various arrangements were studied in a reverberation chamber to determine the absorption coefficient of an auditorium of infinite dimensions. The results were compared to the values of the absorption coefficient measured using the second method, which involved samples enclosed within a frame screening the side surfaces of other auditorium blocks. The results of both methods allowed for the assessment of the sound absorption coefficient of an auditorium of any dimensions while taking into account the sound absorption by the side surfaces. The method developed by the authors will simplify the currently known measurement procedures.

Large venues and auditoriums are commonly associated with their astounding architecture. Their acoustic quality is an essential factor in its qualification as a great and functional, or a badly designed place. However, acoustics is often overlooked during the design stage of a building due to the complexity and high cost of the measurements involved. For this reason, it is important to explore more accessible ways to implement acoustics evaluations. The aim of this work is to compare typical experimental measuring methods and the use of mobile devices to assess the acoustic quality of a room. These measurements are contrasted with the software simulation of the same acoustical space. The results show that the mobile system can be used for professional measurements with low restrictions in the frequency range of interest of this study (90 Hz to 4000 Hz).

The goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are time- and frequency-domain descriptors. English language as an auxiliary language is used in the experiments. In the first part of the experiments, an analysis of Lithuanian and Polish language samples is carried out, features are extracted, and the most discriminating ones are determined. In the second part of the experiments, automatic classification of Lithuanian/English, Polish/English, and Lithuanian/Polish phonemes is performed.

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.