Navigation assistance services for people with visual impairment pose the challenge of providing accurate guidance through non-visual navigation instructions. This paper proposes two techniques to guide the user during navigation assistance, and in particular during turns and straight paths. Both techniques adopt a combination of speech and non-speech audio with the aim of providing continuous, accurate, and unobtrusive guidance. The two solutions differ in the sonification technique used to generate the non-speech audio. The techniques were evaluated in a real-world environment with nine participants having severe visual impairment. Experimental results show that one of the proposed techniques is significantly more effective than a baseline approach adopted in existing solutions, in terms of navigation accuracy during turns and straight paths. Thus, it is a practical and effective solution to the problem of non-visual navigation assistance for people with visual impairment.

People with blindness or severe low vision access mobile devices using screen readers. However, noisy environments can impair screen reader intelligibility. During mobility, this could disorient or even endanger the user. To address this issue, we propose three screen reader speech compensation techniques based on environmental noise: speech rate slowing, adaptive volume increase, and adaptive equalization. Through a study with 12 participants in three simulated noise scenarios, we evaluate screen reader intelligibility and the perceived distraction from the soundscape, with and without compensations. Four of the proposed compensations, in particular those that pair speech rate reduction with volume or equalization adaptation, significantly improve screen reader's speech intelligibility in all the considered scenarios, and the compensations do not have a significant impact on the distraction from the soundscape.

In immersive Audio Augmented Reality, a virtual sound source should be indistinguishable from the existing real ones. This property can be evaluated with the co-immersion criterion, which encompasses scenes constituted by arbitrary configurations of real and virtual objects. Thus, we introduce the term Audio Augmented Virtuality (AAV) to describe a fully virtual environment consisting of auditory content captured from the real world, augmented by synthetic sound generation. We propose an experimental design in AAV investigating how simplified late reverberation (LR) affects the co-immersion of a sound source. Participants listened to simultaneous virtual speakers dynamically rendered through spatial Room Impulse Responses, and were asked to detect the presence of an impostor, i.e., a speaker rendered with one of two simplified LR conditions. Detection rates were found to be close to chance level, especially for one condition, suggesting a limited influence on co-immersion of the simplified LR in the evaluated AAV scenes. This methodology can be straightforwardly extended and applied to different acoustics scenes, complexities, i.e., the number of simultaneous speakers, and rendering parameters in order to further investigate the requirements for immersive audio technologies in AAR and AAV applications.

This paper presents the early results of the project titled "A Band in the Cloud", conducted in cooperation between INDIRE, the agency of the Italian Ministry of Education for educational research and innovation, and LIM, the laboratory of sound and music computing of the University of Milan.The goal of the project is to foster the development of musical and extra-musical skills in young learners through a free web-based digital audio workstation.After presenting the state of the art and discussing the pedagogical aims of the initiative, we will describe the technical details of the platform and give details about the release plan.

A Digital Audio Workstation (DAW) is a hardware and/or software device aiming to ease those operations required for music production, such as arranging, recording, editing, mixing, and, more in general, modifying sounds creatively. A peculiarity of a DAW environment is that most of the work is highly parallelizable, since the basic architecture of a DAW consists in the simultaneous processing of different audio tracks, mainly independent from each other. In order to exploit such a feature, this paper proposes an interface that lets the DAW interact with the Graphics Processing Unit (GPU) in a standardized way. Despite some academic research and experimentation, the professional audio software industry almost never exploited GPUs when implementing entire DAWs, but only when realising very specific tools or third party extensions (plugins). This work also presents and discusses the outcomes of a number of tests conducted in order to choose the optimal architecture. As a result, a GPU-based approach turned to be a valid alternative to the use of CPUs in the computation of audio effects, such as the rendering of audio tracks after mixing and mastering operations, both in real time and offline.

This work presents a dataset of cat vocalizations focusing on the meows emitted in three different contexts: brushing, isolation in an unfamiliar environment, and waiting for food. The dataset contains vocalizations produced by 21 cats belonging to two breeds, namely Maine Coon and European Shorthair. Sounds have been recorded using low-cost devices easily available on the marketplace, and the data acquired are representative of real-world cases both in terms of audio quality and acoustic conditions. The dataset is open-access, released under Creative Commons Attribution 4.0 International licence, and it can be retrieved from the Zenodo web repository.

Abstract This paper explores the behavior of an algorithm called Audio Dynamics Automatic Equalization (ADAE). This algorithm has been inspired by research carried out in the context of image restoration: it is the adaptation of a contrast and color unsupervised equalizer for images, called Automatic Color Equalization (ACE), into the audio domain. Beside testing if the domain shift from image to audio processing can bring some interesting result, this work also investigates if ADAE behaves like already-known technologies for audio manipulation and restoration. To this end, after a description of the original and the derived algorithms, quantitative test are carried out using typical analyses from the Sound and Music Computing literature, such as frequency response, transfer function, and harmonic distortion. Finally, the paper discusses how the algorithm introduces dynamic range adjustments and non-linear distortions, thus behaving like a dynamics processor, a harmonic exciter, and a waveshaper.

This paper proposes a methodology to assess the accessibility for blind or visually impaired people of music production software known as Digital Audio Workstations.The products chosen for the tests are Cockos REAPER, Avid Pro Tools, and Steinberg Cubase, three of the most popular solutions falling in this category.Both Microsoft Windows and macOS versions were tested, since these two operating systems natively integrate assistive technologies which provide a further layer to be considered.The degree of accessibility was evaluated in relation to the possibility for blind or visually impaired people to invoke key functions and perform basic operations.Finally, a focus group with visually impaired professional music producers was organized in order to assess the proposed evaluation methodology.

Independent mobility is one of the main challenges for blind or visually impaired (BVI) people. In particular, BVI people often need to identify and avoid nearby obstacles, for example a bicycle parked on the sidewalk. This is generally achieved with a combination of residual vision, hearing and haptic sensing using the white cane. However, in many cases, BVI people can only perceive obstacles at short distance (typically about 1m, i.e., the white cane detection range), in other situations obstacles are hard to detect (e.g., those elevated from the ground), while others should not be hit by the white cane (e.g., a standing person). Thus, some time and effort are required to identify the object in order to understand how to avoid it. A solution to these problems can be found in recent computer vision techniques that can run on mobile and wearable devices to detect obstacles at a distance. However, in addition to detecting obstacles, it is also necessary to convey information about them to a BVI user. This contribution presents WatchOut, a sonification technique for conveying real-time information about the main characteristics of an obstacle to a BVI person, who can then use this additional feedback to safely navigate in the environment. WatchOut was designed with a user-centric approach, involving two iterations of online questionnaires with BVI participants in order to define, improve and evaluate the sonification technique. WatchOut was implemented and tested as a module of a mobile app that detects obstacles using state-of-the-art computer vision technology. Results show that the system is considered usable, and can guide the users to avoid more than 85% of the obstacles.

Indoor navigation services for people with visual impairment are being researched in academia, and working systems have already been deployed in public places. While previous research mainly focuses on computing the user's position with high accuracy, providing non-visual navigation instructions is also a challenge and naive approaches can fail in helping users reach their target destination or even expose them to hazards.In this paper we investigate the problem of guiding users to rotate towards a target direction. We propose three different sonification techniques that provide continuous guidance during rotation, and we compare them to a single-impulse baseline, used in previous works. We also explore three variations that reinforce the proposed techniques by combining them with the baseline. A preliminary study with 10 blind participants highlights two dominant techniques, which we analyze through a follow-up study with 18 participants, from 2 groups with very distant cultural backgrounds. While stark differences emerge in the performance from the two groups, we highlight two clear results common to both: 1) one of the proposed techniques significantly outperforms the baseline, reducing the average rotation error by a factor of 3.5 (from 11° to 3°); 2) the interaction speed of this technique, generally slower than the baseline, significantly improves when combined with the baseline technique.

Indoor navigation is an important service, currently investigated both in industry and academia. While the main focus of research is the computation of users' position, the additional challenge of conveying guidance instructions arises when the target user is blind or visually impaired (BVI). This contribution presents our ongoing research aimed at adopting sonification techniques to guide a BVI person. In particular we introduce three sonification techniques to guide the user during rotations. Preliminary results, conducted with 7 BVI people, show that some of the proposed sonification technique outperform a benchmark solution adopted in previous contributions.

Within a Music Information Retrieval perspective, the goal of the study presented here is to investigate the impact on sound features of the musician's affective intention, namely when trying to intentionally convey emotional contents via expressiveness. A preliminary experiment has been performed involving 10 tuba players. The recordings have been analysed by extracting a variety of features, which have been subsequently evaluated by combining both classic and machine learning statistical techniques. Results are reported and discussed.