Modelling, Simulation and Data Analysis in Acoustical Problems

Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years

Cough Monitoring Through Audio Analysis

The detection of cough events in audio recordings requires the analysis of a significant amount of data as cough is typically monitored continuously over several hours to capture naturally occurring cough events. The recorded data is mostly composed of undesired sound events such as silence, background noise, and speech. To reduce computational costs and to address the ethical concerns raised from the collection of audio data in public environments, the data requires pre-processing prior to any further analysis. Current cough detection algorithms typically use pre-processing methods to remove undesired audio segments from the collected data but do not preserve the privacy of individuals being recorded while monitoring respiratory events. This study reveals the need for an automatic pre-processing method that removes sensitive data from the recording prior to any further analysis to ensure privacy preservation of individuals. Specific characteristics of cough sounds can be used to discard sensitive data from audio recordings at a pre-processing stage, improving privacy preservation, and decreasing ethical concerns when dealing with cough monitoring through audio analysis. We propose a pre-processing algorithm that increases privacy preservation and significantly decreases the amount of data to be analysed, by separating cough segments from other non-cough segments, including speech, in audio recordings. Our method verifies the presence of signal energy in both lower and higher frequency regions and discards segments whose energy concentrates only on one of them. The method is iteratively applied on the same data to increase the percentage of data reduction and privacy preservation. We evaluated the performance of our algorithm using several hours of audio recordings with manually pre-annotated cough and speech events. Our results showed that 5 iterations of the proposed method can discard up to 88.94% of the speech content present in the recordings, allowing for a strong privacy preservation while considerably reducing the amount of data to be further analysed by 91.79%. The data reduction and privacy preservation achievements of the proposed pre-processing algorithm offers the possibility to use larger datasets captured in public environments and would beneficiate all cough detection algorithms by preserving the privacy of subjects and by-stander conversations recorded during cough monitoring

Outlook Magazine, Winter 1988

https://digitalcommons.wustl.edu/outlook/1091/thumbnail.jp

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the newborn to the adult and elderly. Over the years the initial issues have grown and spread also in other fields of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years in Firenze, Italy. This edition celebrates twenty-two years of uninterrupted and successful research in the field of voice analysis