@phdthesis{Ackermann2024, author = {Ackermann, David}, title = {Dynamic Sound Sources for Virtual Acoustic Reality: Description, Implementation and Evaluation}, publisher = {TU Berlin}, address = {Berlin}, doi = {10.14279/depositonce-19949}, school = {Hochschule D{\"u}sseldorf}, year = {2024}, abstract = {terns, especially those presented by natural sources such as musical instruments or human voices, is crucial. While static sound sources, such as loudspeakers, have a relatively consistent acoustic footprint, dynamic sources present a multi-faceted set of challenges. Musical instruments, for example, have dynamic radiation patterns. The directivity of these instruments changes not only with frequency, but also with the specific note being played, and with the performer's gestures. These dynamic effects of directivity influences both the perceived loudness and the timbre at a given location within the audience and shapes the spatial characteristics of the sound field produced. This modulation is crucial when recreating authentic acoustic environments, whether in a virtual environment or in real-world architectural designs. Essentially, for an acoustic simulation to be considered accurate, it must capture these nuances. The intricate interplay of directivity, pitch and motion significantly shapes the listening experience and requires deeper integration of these elements into future simulations and designs.}, subject = {Musikalische Akustik}, language = {en} } @phdthesis{Versuemer2025, author = {Vers{\"u}mer, Siegbert}, title = {Generalized prediction of quiet indoor soundscapes based on retrospective and in-situ judgements}, publisher = {Berlin}, address = {Technische Universit{\"a}t Berlin}, doi = {10.14279/depositonce-23962}, pages = {199}, year = {2025}, abstract = {This dissertation aims to enhance the understanding of how people perceive and react to everyday sounds, particularly in their homes. The focus is laid on indoor soundscapes and the interplay between acoustic measures, individual differences, and contextual factors. A retrospective online study and a field study at peoples' homes based on the Experience Sampling Method were the ecologically valid ground truth for four key publications. These address significant gaps in soundscape research by providing insights into the factors influencing sound perception in real-life contexts, the evaluation of low-level (i.e., quiet) sounds, and the consequences of (in)appropriate statistical analysis of imbalanced hierarchical soundscape data. The studies reveal that the sound source category is a critical predictor of annoyance and the pleasantness of soundscapes, with different types of sounds (e.g., natural, human, technical) having distinct impacts. Contrary, the effect of acoustic measures like perceived and calculated loudness on sound perception was expected to be high but was masked by contextual factors. These were the perceived control over the acoustic situation and the affective state of a person in the specific situation, proving context-related perceptual measures to be more important than the sound itself. The research consequently highlights the need for automatic sound source identification in complex polyphony everyday sound environments and suggests that individual preferences and liking of sounds could be potential factors in predicting individual sound perception. The dissertation also emphasizes the importance of using appropriate statistical methods, including mixed-effects models and nonlinear regression techniques, to generate more generalizable and more valid results based on hierarchical and imbalanced soundscape data. The findings underscore the limitations of traditional acoustic metrics and advocate for the use of time-series data to better capture the dynamic nature of everyday sound environments in contrast to stimuli typically used in laboratory studies. The author further developed a multi-objective function for avoiding both over- and underfitting during hyperparameter tuning, significantly improving generalized model fitting in soundscape research. Overall, this work contributes to the field of soundscape research by providing a comprehensive analysis of sound perception in indoor environments, highlighting the importance of context, individual differences, and advanced statistical methods in understanding and modeling soundscapes. Finally, future perspectives were discussed, such as the focus on individual preferences, experiences, and expectations for the improved prediction of individual sound perception.}, subject = {Psychoakustik}, language = {en} } @phdthesis{Krieter2020, author = {Krieter, Philipp}, title = {Looking Inside - Mobile Screen Recordings as a Privacy Friendly Long-Term Data Source to Analyze User Behavior}, publisher = {Bremen}, address = {Universit{\"a}t Bremen}, doi = {10.26092/elib/103}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:46-elib43189}, year = {2020}, abstract = {Mobile devices are ubiquitous in many societies and shape the way we interact with technology and each other. Research on how we use and perceive technology is essential to understand its impact. This work advances how we can follow user behavior on mobile devices. We combine the strength of two common data sources for tracking on mobile devices, log files, and screen recordings. Log files are suitable for long-term and privacy-friendly analyzation but provide rather general data (e.g. system log files) unless one has access to the source code of the applications or operating systems. Screen recordings are usually used for short-termed analysis (e.g. usability tests) because the analysis is time-consuming, but they provide all activities on the screen in high detail regardless of which application or operating system. This thesis combines both data sources and presents an approach to automatically generate log files from mobile screen recordings. The approach utilizes methods of computer vision and machine learning to automatically process screen recordings and extend their use. Screen recordings reveal virtually everything a user does with a device, making privacy important, especially in user studies. We present a privacy concept and implementation and show how the risk of exposing private data can be reduced, by processing all recordings locally on the mobile devices and anonymizing the resulting log files. In order to apply the developed method in practice, we carry out a study in the context of education and show how log files of screen recordings can complement and extend existing research in learning analytics. This thesis opens up novel perspectives on how we can look at human-computer interaction with mobile devices. We show how to generate long-term log data with high detail and accuracy from mobile screen recordings, in a privacy-friendly way, locally on mobile devices.}, language = {en} } @phdthesis{Franz2010, author = {Franz, Thomas}, title = {Semantic Personal Information Management}, publisher = {Universit{\"a}t Koblenz-Landau}, address = {M{\"u}nchen}, isbn = {978-3-86853-706-2}, year = {2010}, language = {en} } @phdthesis{Steffens2013, author = {Steffens, Jochen}, title = {"Wie viel Realit{\"a}t braucht der Mensch?" - Untersuchungen zum Einfluss der Versuchsumgebung auf die Ger{\"a}uschbeurteilung von Haushaltsger{\"a}ten}, publisher = {Technische Universit{\"a}t}, address = {Berlin}, organization = {Technische Universit{\"a}t}, doi = {10.14279/depositonce-3732}, year = {2013}, language = {de} } @phdthesis{Herder1999, author = {Herder, Jens}, title = {A Sound Spatialization Resource Management Framework}, publisher = {University of Tsukuba}, address = {Tsukuba}, organization = {University of Tsukuba}, year = {1999}, abstract = {In a virtual reality environment, users are immersed in a scene with objects which might produce sound. The responsibility of a VR environment is to present these objects, but a practical system has only limited resources, including spatialization channels (mixels), MIDI/audio channels, and processing power. A sound spatialization resource manager, introduced in this thesis, controls sound resources and optimizes fidelity (presence) under given conditions, using a priority scheme based on psychoacoustics. Objects which are spatially close together can be coalesced by a novel clustering algorithm, which considers listener localization errors. Application programmers and VR scene designers are freed from the burden of assigning mixels and predicting sound source locations. The framework includes an abstract interface for sound spatialization backends, an API for the VR environments, and multimedia authoring tools.}, language = {en} }