Mapping Acoustic and Semantic Dimensions of Auditory Perception

Auditory categorisation is a function of sensory perception which allows humans to generalise across many different sounds present in the environment and classify them into behaviourally relevant categories. These categories cover not only the variance of acoustic properties of the signal but also a wide variety of sound sources. However, it is unclear to what extent the acoustic structure of sound is associated with, and conveys, different facets of semantic category information. Whether people use such data and what drives their decisions when both acoustic and semantic information about the sound is available, also remains unknown. To answer these questions, we used the existing methods broadly practised in linguistics, acoustics and cognitive science, and bridged these domains by delineating their shared space. Firstly, we took a model-free exploratory approach to examine the underlying structure and inherent patterns in our dataset. To this end, we ran principal components, clustering and multidimensional scaling analyses. At the same time, we drew sound labels’ semantic space topography based on corpus-based word embeddings vectors. We then built an LDA model predicting class membership and compared the model-free approach and model predictions with the actual taxonomy. Finally, by conducting a series of web-based behavioural experiments, we investigated whether acoustic and semantic topographies relate to perceptual judgements. This analysis pipeline showed that natural sound categories could be successfully predicted based on the acoustic information alone and that perception of natural sound categories has some acoustic grounding. Results from our studies help to recognise the role of physical sound characteristics and their meaning in the process of sound perception and give an invaluable insight into the mechanisms governing the machine-based and human classifications

Music-listening systems

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2000.Includes bibliographical references (p. [235]-248).When human listeners are confronted with musical sounds, they rapidly and automatically orient themselves in the music. Even musically untrained listeners have an exceptional ability to make rapid judgments about music from very short examples, such as determining the music's style, performer, beat, complexity, and emotional impact. However, there are presently no theories of music perception that can explain this behavior, and it has proven very difficult to build computer music-analysis tools with similar capabilities. This dissertation examines the psychoacoustic origins of the early stages of music listening in humans, using both experimental and computer-modeling approaches. The results of this research enable the construction of automatic machine-listening systems that can make human-like judgments about short musical stimuli. New models are presented that explain the perception of musical tempo, the perceived segmentation of sound scenes into multiple auditory images, and the extraction of musical features from complex musical sounds. These models are implemented as signal-processing and pattern-recognition computer programs, using the principle of understanding without separation. Two experiments with human listeners study the rapid assignment of high-level judgments to musical stimuli, and it is demonstrated that many of the experimental results can be explained with a multiple-regression model on the extracted musical features. From a theoretical standpoint, the thesis shows how theories of music perception can be grounded in a principled way upon psychoacoustic models in a computational-auditory-scene-analysis framework. Further, the perceptual theory presented is more relevant to everyday listeners and situations than are previous cognitive-structuralist approaches to music perception and cognition. From a practical standpoint, the various models form a set of computer signal-processing and pattern-recognition tools that can mimic human perceptual abilities on a variety of musical tasks such as tapping along with the beat, parsing music into sections, making semantic judgments about musical examples, and estimating the similarity of two pieces of music.Eric D. Scheirer.Ph.D

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

6th International Probabilistic Workshop - 32. Darmstädter Massivbauseminar: 26-27 November 2008 ; Darmstadt, Germany 2008 ; Technische Universität Darmstadt

These are the proceedings of the 6th International Probabilistic Workshop, formerly known as Dresden Probabilistic Symposium or International Probabilistic Symposium. The workshop was held twice in Dresden, then it moved to Vienna, Berlin, Ghent and finally to Darmstadt in 2008. All of the conference cities feature some specialities. However, Darmstadt features a very special property: The element number 110 was named Darmstadtium after Darmstadt: There are only very few cities worldwide after which a chemical element is named. The high element number 110 of Darmstadtium indicates, that much research is still required and carried out. This is also true for the issue of probabilistic safety concepts in engineering. Although the history of probabilistic safety concepts can be traced back nearly 90 years, for the practical applications a long way to go still remains. This is not a disadvantage. Just as research chemists strive to discover new element properties, with the application of new probabilistic techniques we may advance the properties of structures substantially. (Auszug aus Vorwort

Ecology-based planning. Italian and French experimentations

This paper examines some French and Italian experimentations of green infrastructures’ (GI) construction in relation to their techniques and methodologies. The construction of a multifunctional green infrastructure can lead to the generation of a number of relevant bene fi ts able to face the increasing challenges of climate change and resilience (for example, social, ecological and environmental through the recognition of the concept of ecosystem services) and could ease the achievement of a performance-based approach. This approach, differently from the traditional prescriptive one, helps to attain a better and more fl exible land-use integration. In both countries, GI play an important role in contrasting land take and, for their adaptive and cross-scale nature, they help to generate a res ilient approach to urban plans and projects. Due to their fl exible and site-based nature, GI can be adapted, even if through different methodologies and approaches, both to urban and extra-urban contexts. On one hand, France, through its strong national policy on ecological networks, recognizes them as one of the major planning strategies toward a more sustainable development of territories; on the other hand, Italy has no national policy and Regions still have a hard time integrating them in already existing planning tools. In this perspective, Italian experimentations on GI construction appear to be a simple and sporadic add-on of urban and regional plans

Time Localization of Abrupt Changes in Cutting Process using Hilbert Huang Transform

Cutting process is extremely dynamical process influenced by different phenomena such as chip formation, dynamical responses and condition of machining system elements. Different phenomena in cutting zone have signatures in different frequency bands in signal acquired during process monitoring. The time localization of signal’s frequency content is very important. An emerging technique for simultaneous analysis of the signal in time and frequency domain that can be used for time localization of frequency is Hilbert Huang Transform (HHT). It is based on empirical mode decomposition (EMD) of the signal into intrinsic mode functions (IMFs) as simple oscillatory modes. IMFs obtained using EMD can be processed using Hilbert Transform and instantaneous frequency of the signal can be computed. This paper gives a methodology for time localization of cutting process stop during intermittent turning. Cutting process stop leads to abrupt changes in acquired signal correlated to certain frequency band. The frequency band related to abrupt changes is localized in time using HHT. The potentials and limitations of HHT application in machining process monitoring are shown