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In natural environments, the auditory system is typically confronted with a mixture of sounds originating from different sound sources. As sounds spread over time, the auditory system has to continuously decompose competing sounds into distinct meaningful auditory objects or “auditory streams” referring to certain sound sources. This decomposition work, which was termed by Albert Bregman as “Auditory scene analysis” (ASA), involves two kinds of grouping to be done. Grouping based on simultaneous cues, such as harmonicity and on sequential cues, such as similarity in acoustic features over time. Understanding how the brain solves these tasks is a fundamental challenge facing auditory scientist. In recent years, the topic of ASA was broadly investigated in different fields of auditory research, including a wide range of methods, studies in different species, and modeling. Despite the advance in understanding ASA, it still proves to be a major challenge for auditory research. This includes verifying whether experimental findings are transferable to more realistic auditory scenes. A central approach in understanding ASA is the use of certain stimulus parameters that produce an ambiguous percept. The advantage of such an approach is that different perceptual organizations can be studied without varying physical stimulus parameters. Additionally, the perception of ambiguous stimuli can be volitionally controlled by intention or task. By using this one can mirror real hearing situations where listeners intent to identify and to localize auditory sources. Recently it was also found that in classical auditory streaming sequences perceptual ambiguity was not restricted to but was observed over a broad range of stimulus parameters. The proposed Research Topic pursues to bring together scientist in the different fields of auditory research whose work addresses the issue of perceptual ambiguity. Researchers were welcome to contribute experimental reports, computational modeling, and reviews that consider auditory ambiguity in its modality specific characteristics as well as in comparison to visual ambiguous figures. The overall goal of contributions was to consider the experimental findings from the perspective of real auditory scenes. In a broader sense, the Research Topic was open for contributions which are related to the issue of active listening in complex scenes.

Hearing. --- Auditory pathways. --- Ear. --- ambiguity --- Multistable Perception --- auditory scene analysis --- realistic auditory scenes --- stream segregation --- ambiguity --- Multistable Perception --- auditory scene analysis --- realistic auditory scenes --- stream segregation

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The interpretation of aerial and satellite imagery requires significant experience and expert knowledge and therefore is mainly performed by professional image interpreters. So far, automatic methods are not able to provide comparable results but they can be used to support the manual image interpretation process. This work shows how the benefits of manual and automatic image interpretation can be adequately combined in an interactive image interpretation system.

Luftbildauswertung --- Fernerkundung --- Szenenanalyse --- Unterstützungssysteme --- Bildverstehenremote sensing --- image understanding --- decision support systems --- image interpretation --- scene analysis

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In natural environments, the auditory system is typically confronted with a mixture of sounds originating from different sound sources. As sounds spread over time, the auditory system has to continuously decompose competing sounds into distinct meaningful auditory objects or “auditory streams” referring to certain sound sources. This decomposition work, which was termed by Albert Bregman as “Auditory scene analysis” (ASA), involves two kinds of grouping to be done. Grouping based on simultaneous cues, such as harmonicity and on sequential cues, such as similarity in acoustic features over time. Understanding how the brain solves these tasks is a fundamental challenge facing auditory scientist. In recent years, the topic of ASA was broadly investigated in different fields of auditory research, including a wide range of methods, studies in different species, and modeling. Despite the advance in understanding ASA, it still proves to be a major challenge for auditory research. This includes verifying whether experimental findings are transferable to more realistic auditory scenes. A central approach in understanding ASA is the use of certain stimulus parameters that produce an ambiguous percept. The advantage of such an approach is that different perceptual organizations can be studied without varying physical stimulus parameters. Additionally, the perception of ambiguous stimuli can be volitionally controlled by intention or task. By using this one can mirror real hearing situations where listeners intent to identify and to localize auditory sources. Recently it was also found that in classical auditory streaming sequences perceptual ambiguity was not restricted to but was observed over a broad range of stimulus parameters. The proposed Research Topic pursues to bring together scientist in the different fields of auditory research whose work addresses the issue of perceptual ambiguity. Researchers were welcome to contribute experimental reports, computational modeling, and reviews that consider auditory ambiguity in its modality specific characteristics as well as in comparison to visual ambiguous figures. The overall goal of contributions was to consider the experimental findings from the perspective of real auditory scenes. In a broader sense, the Research Topic was open for contributions which are related to the issue of active listening in complex scenes.

Hearing. --- Auditory pathways. --- Ear. --- ambiguity --- Multistable Perception --- auditory scene analysis --- realistic auditory scenes --- stream segregation

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Computational auditory scene analysis. --- Computer sound processing. --- Content analysis (Communication) --- Data processing.

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Introduction to Audio Analysis serves as a standalone introduction to audio analysis, providing theoretical background to many state-of-the-art techniques. It covers the essential theory necessary to develop audio engineering applications, but also uses programming techniques, notably MATLAB®, to take a more applied approach to the topic. Basic theory and reproducible experiments are combined to demonstrate theoretical concepts from a practical point of view and provide a solid foundation in the field of audio analysis. Audio feature extraction, audio classification, audio se

Audio. --- MATLAB. --- Signal processing -- Digital techniques -- Data processing. --- Computer sound processing --- Computational auditory scene analysis --- Numerical analysis --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Electrical Engineering --- Computer programs --- Computer sound processing. --- Computational auditory scene analysis. --- Content analysis (Communication) --- Data processing. --- Auditory scene analysis --- CASA (Sound analysis) --- Sound processing, Computer --- Electronic digital computers --- Sound --- Computer programs. --- Data processing --- Recording and reproducing --- Digital techniques --- MATLAB (Computer program) --- Matrix laboratory --- MATLAB (Computer file)