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Probabilistic graphical models are a powerful concept for representing complex relations between components in systems with uncertain behavior. Stemming originally from statistical mechanics, their applications stretch across various fields such as computer vision, speech recognition, social network analysis, and many more. Often they allow for a compact formulation of practical challenges in terms of fundamental…

This doctoral thesis treats data-driven methodologies to enhance the performance of anomaly detection and virtualization in the context of engine control. Anomalies, specifically knocking combustion pose the major obstacle towards optimal thermal efficiency of an engine and considerable risk of critical damages, thus their detection assumes a priority role for meeting future regulatory targets for…

This thesis presents a corpus-based, comparative analysis of error patterns in human and automatic speech recognition (ASR based on utterances taken from spontaneous, unscripted face-to-face conversations. The utterances reflect specific patterns that are characteristic of this speaking style: They are disfluent through either a pause, a filler particle (FP), a break in the syntax, or…

The central topic of this thesis is Reverberation. Reverberation is used as a global term to describe a series of physical and perceptual phenomena that occur in enclosed environments and relate to the acoustical interaction between a sound source and the enclosure. This work focuses on the effects of reverberation that are likely to occur…

Large vocabulary continuous speech recognition (LVCSR) systems require large amounts of labelled audio data for training. While such literal transcriptions of audio recordings, i.e., highly accurate textual reproductions of the utterances are expensive and therefore only avail- able in limited amounts, non-literal field data from commercial automatic dictation systems can be collected on large scale…

When considering the acoustics of a room as a linear time-invariant system, the room impulse response (RIR) describes the response of the room to an audio signal from a given source position to a given receiver position. If the RIR is perfectly known, the response of the room to any acoustic signal can be predicted….

The spatial information contained in recorded microphone signals has a fundamental role in the characterization of acoustic environments. Furthermore, it can be exploited in digital audio processing frameworks for enhancing a desired source signal, benefiting applications such as hands-free telephony, hearing devices, human-machine interfaces and acoustic monitoring systems. Despite its acknowledged relevance, accurately estimating and…

Historical worship spaces, such as churches, cathedrals, mosques, and temples, possess unique acoustics that shaped the way rituals and music were developed and performed in these spaces. The acoustics of these spaces are often at risk due to renovations, structural decay, natural disasters, and changing usage patterns. This thesis explores how the acoustics of historical…

Consciousness is a multifaceted construct that spans a continuum from wakefulness?characterized by responsiveness to external stimuli and cognitive engagement?to altered states, such as fatigue, sleep, and anesthesia, where individuals may experience decreased cognitive function or difficulty being easily aroused. Given its wide range of real-life applications and its origin in brain, a significant amount of…

Positioning and timing information is fundamental for our daily lives in today?s society. Our society uses this information in many applications such as telecommunication networks, energy grids and general navigation applications. Today this crucial information is mainly derived from the global navigation satellite system. Due to the low signal strength, this signal is prone to…