Deep Neural Network Approaches for Selective Hearing based on Spatial Data Simulation

Selective Hearing (SH) refers to the listener’s attention to specific sound sources of interest in their auditory scene. Achieving SH through computational means involves detection, classification, separation, localization and enhancement of sound sources. Deep neural networks (DNNs) have been shown to perform these tasks in a robust and time-efficient manner. A promising application of SH are intelligent noise-cancelling headphones, where sound sources of interest, such as warning signals, sirens or speech, are extracted from a given auditory scene and conveyed to the user, whilst the rest of the auditory scene remains inaudible. For this purpose, existing noise cancellation approaches need to be combined with machine learning techniques. In this context, we evaluate a convolutional neural network (CNN) architecture and a long short-term memory (LSTM) architecture for the detection and separation of sirens. In addition, we propose a data simulation approach for generating different sound environments for a virtual pair of headphone microphones. The Fraunhofer SpatialSound Wave technology is used for a realistic evaluation of the trained models. For the evaluation, a three-dimensional acoustic scene is simulated via the object-based audio approach

Hörbarmachung von Lärmschutzmaßnahmen

Lärm zählt zu einem der relevantesten umweltbedingten Gesundheitsrisiken und wirkt sich nachweislich negativ auf die Gesundheit und das Wohlbefinden des Menschen aus. Die Relevanz des Themas zeigt sich durch die aktuellen Richtlinien der WHO, die eine explizite Einbindung der von Veränderung in der Lärmbelastung betroffenen Teilen der Bevölkerung fordert [1]. In der Verkehrswegeplanung ist die Verwendung von softwarebasierten Simulationswerkzeugen zur Vorhersage der erwarteten Lärmbelastung Stand der Technik. Die Berechnung von erwarteten Beurteilungspegeln an Verkehrswegen erfolgt auf Basis zahlreicher Kennwerte gemäß Bundes-Immissionsschutzgesetz [2]. Hierbei handelt es sich typischerweise um Mittelungspegel, die Lärmereignisse, welche in einem gewissen Zeitraum stattfinden, nur durch einen Pegelwert ausdrücken. Gerade bei der Planung von Schallschutzwänden ist es dem Laien jedoch nicht möglich, sich die Auswirkungen der errechneten Pegelabnahmen vorzustellen. Visuelle Darstellungen in Form von Lärmkarten helfen dabei nur wenig, da Lärm individuell empfunden wird. Um die Wirkung von Schallschutzmaßnahmen erlebbar zu machen, und so eine wirkliche Einbeziehung von Teilen der Bevölkerung zu ermöglichen, muss das zu erwartende Resultat realitätsnah hörbar gemacht werden. Da das Gehör richtungsselektiv funktioniert, ist es notwendig, nicht nur den Pegel an einer Position, sondern seine räumliche Ausdehnung wiederzugeben. In dieser Arbeit wird ein erster Prototyp vorgestellt, der es erlaubt, die räumliche Ausdehnung von Schallschutzmaßnahmen interaktiv hörbar zu machen

An Approach for Object-Based Spatial Audio Mastering

Object-based spatial audio is an approach for interactive three-dimensional audio reproduction. This concept not only changes how creators interact with audio content, but also how it is saved and transmitted. Hence, a new process in the reproduction chain called rendering was established. The rendering process generates loudspeaker signals out of an object-based scene. Although recording and mixing have been subject to research in recent years, concepts for object-based mastering are nearly missing. The main difference compared to channel-based mastering is that instead of adjusting loudspeaker channels, audio objects need to be altered. This requires a fundamentally new concept for mastering. In this paper, a new method for mastering object-based audio is presented

Immersive Object-Based Mastering

To date, object-based spatial audio has been subject to much research, and a few production tools have entered the market. The main difference to the channel-based audio paradigm is that object-based spatial audio enables engineers to create three-dimensional audio scenes regardless of any particular loudspeaker setup. To playback audio scenes, a separate rendering process calculates all loudspeaker signals in real time, based on the meta data of audio objects in a scene. While the authoring process of an audio scene can be easily connected to conventional audio recording and mixing processes, possibilities for mastering audio scenes are still very limited. The main limitation stems from the aspect that compared to channel-based mastering, no loudspeaker channels can be altered. However, instead of always altering audio objects individually, the meta data part of audio objects can be used to provide engineers with convenient tools for object-based spatial mastering as well. Beyond solely mastering the audio data of a scene, new tools can also alter the meta data of audio objects on a global level for meta data mastering. These new object-based spatial mastering techniques are presented

Application of wave field synthesis in virtual acoustic engineering

State-of-the-art product design processes are driven by virtual reality (VR) technologies. However VR technologies these days are often limited to visualization only. Due to the lack of robust psychoacoustic models that predict parameters like pleasantness of audio signals, a plausible auralisation of product sound is mandatory. Modern sound reproduction techniques, such as wave field synthesis (WFS), can help us to embed an appropriate acoustical environment in virtual engineering. Possible use cases are noise reduction, sound design, sound branding, product presentation as well as soundscape planning. WFS is a sound reproduction technique for physical synthesis of a virtual sound field. In contrast to stereo or surround sound, it is possible with WFS to overcome the ”sweet spot” problem which is essential for interactive multi-user VR systems. Currently this technology is mainly used in entertainment applications. This paper introduces a concept and a prototypical implementation of an object-based acoustical environment for virtual engineering. It is designed for the auralisation of both single sources as well as complex sound scenes by means of up-to-date wave field synthesis technologies. The presented system covers latest developments in spatial audio reproduction, e.g. auralization of directional sources, interactive real-time room acoustic simulation and an intuitive user interface