According to Italian regulation, the Ministerial Decree of 11 October 2017 about Environmental Criteria, reference values for acoustic indoor quality descriptors in public buildings are imposed. Regarding school environments, indoor acoustic quality targets refer to reverberation time, clarity, and speech intelligibility, whose representative acoustic descriptor is the speech transmission index (STI). This paper presents pyeSTImate, a Python-based tool for speech transmission index prediction in lecture rooms. The tool returns fully simulated results from the dimensions and material characteristics of classrooms with parallelepiped geometry and without limitations in size. Extensive experiments have been conducted with different simulation methods, evaluating the accuracy by comparison with in situ measurements selected from primary, secondary, and university classrooms in school buildings of the Marche Region in Italy. The combination of simulated speech transmission indexes with a prediction method based on an artificial neural network has also been evaluated. The analysis of the performance demonstrates the computational robustness of the tool that enables its use for the analysis of existing rooms, as well as for the renovation and design of new spaces.

In this paper, an alternative method for the calculation of masonry walls sound insulation is investigated. Thirty-four simple monolithic brick walls were examined. For the considered walls, the measurements made by accredited laboratories in compliance with ISO 10140 standard were collected. For each building element, the experimental measurements and all the information concerning the geometric and physical characteristics of all the components (material, dimensions, mass, density, Young’s modulus, Poisson’s module, hole content, etc.) were classified. Then, from the collection of measurements obtained in the standard laboratories and the division of them into homogeneous groups, a statistical sensitivity analysis to determine the most statistically significant parameter for the sound insulation of building walls was carried out. This analysis was a useful tool for selecting parameters to be used in forecast models and for calculating statistical effects. Finally, an alternative method based on the use of artificial neural networks (ANN) was proposed. This paper discusses the results obtained by applying the models to a specific kind of construction: the masonry walls. The results will show a good correlation of the values obtained on this first type of building construction. This encourages the extension of the method explained in this work to other types of walls.

Heating ventilation and air conditioning (HVAC) systems represent one of the main noise sources inside classrooms. This explain why HVAC systems require careful design, competent installation and balancing, and regular maintenance. Many factors influence the classroom acoustical design, such as air handlers or fans, the velocity of air inside the classroom, as well as the size and acoustical treatment of ducts, returns, and diffusers. Acoustic parameters, including background-noise levels, reverberation time, and intelligibility, were analyzed in 17 classrooms at the Università Politecnica in the Marche region. The study of intelligibility was performed by measuring the objective parameters in situ and using prediction methods to determine the intelligibility score. The relationship between speech intelligibility measurements and speech intelligibility calculation has been studied. The relationship between the STI values with the background-noise levels and the reverberation time was also studied. This research shows that a comparison between predictive methods and measurement methods results in speech intelligibility for classrooms of different sizes with and without HVAC systems. The current method of calculating the voice transmission index (STI), proposed by national and international standards, has been used to determine speech intelligibility scores in classrooms. The results show that the calculation tool has computational robustness allowing its use in preliminary evaluations of speech intelligibility, design of the optimal type of school buildings, and sound amplification systems in classrooms that comply with Italian regulations.

There is a growing scientific consensus that COVID-19 could be transmitted through the airborne route, putting ventilation at the heart of a mitigation strategy for buildings, including schools. The design of suitable systems requires to consider all aspects both for the control of air movement and the diffusion of bacterial loads, but also of other parameters of indoor air quality. This work examines the acoustic design of ventilation systems in schools and the effects that the systems have on the acoustic quality of the classrooms in compliance with the standard series UNI 11532. The standards provide a guideline on the design and the evaluation of the acoustic performances of schools, including attention for children with special educational needs. In particular, the case study refers to classrooms in the University Politecnica delle Marche, Ancona

Today, the art of knowing how to listen is more urgent than ever. The perceptive sound system of the human being is stimulated daily by countless artificial sounds that dominate natural ones. When it comes to the idea of the soundscape, the terminology was initially referred to by composer and environmentalist Raymond Murray Shafer, who defined “soundscape” as a relationship between the ear, humans, built environments, and society. This paper aims to apply the sound landscape approach in the seaport area of Ancona (Italy); a large area, frequented daily by many people, which is divided into passenger and ferry terminals, container terminals, plants for solid bulk, and commercial and recreational activities. The purpose of the study was to evaluate the perception that a human has of the urban layout of the port area by correlating the parameters of traditional acoustics with psychoacoustics. To evaluate the subjective parameters, a questionnaire was developed and applied, enabling the analysis of demographic and behavioral factors such as age, visit frequency, and length of stay of the participants in the clusters of the seaport. This way, it was possible to give an indication of the sound quality of the different clusters of the port area, from an acoustic and emotional point of view, and this information could be particularly helpful in the planning phase of new attractions for the Ancona seaport.