The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Juan Pablo Bello - One of the best experts on this subject based on the ideXlab platform.
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Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research
IEEE Signal Processing Magazine, 2019Co-Authors: Brian Mcfee, Mark Cartwright, Justin Salamon, Rachel M. Bittner, Juan Pablo BelloAbstract:In the early years of music information retrieval (MIR), research problems were often centered around conceptually simple tasks, and methods were evaluated on small, idealized data sets. A canonical example of this is genre recognition-i.e., Which one of n genres describes this song?-which was often evaluated on the GTZAN data set (1,000 musical excerpts balanced across ten genres) [1]. As task definitions were simple, so too were signal analysis pipelines, which often derived from methods for speech processing and recognition and typically consisted of simple methods for feature extraction, statistical modeling, and evaluation. When describing a research system, the expected level of detail was superficial: it was sufficient to state, e.g., the number of mel-frequency cepstral coefficients used, the statistical model (e.g., a Gaussian mixture model), the choice of data set, and the evaluation criteria, without stating the underlying software dependencies or implementation details. Because of an increased abundance of methods, the proliferation of software toolkits, the explosion of machine learning, and a focus shift toward more realistic problem settings, modern research systems are substantially more complex than their predecessors. Modern MIR researchers must Pay Careful Attention to detail when processing metadata, implementing evaluation criteria, and disseminating results.
Josh Tenenberg - One of the best experts on this subject based on the ideXlab platform.
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A blind person's interactions with technology
Communications of the ACM, 2009Co-Authors: Kristen Shinohara, Josh TenenbergAbstract:Meaning can be as important as usability in the design of technology. CURRENT PRACTICE IN computer interface design often takes for granted the user’s sightedness. But a blind user employs a combination of other senses in accomplishing everyday tasks, such as having text read aloud or using fingers along a tactile surface to read Braille. As such, designers of assistive technologies must Pay Careful Attention to the alternatives to sight to engage a blind user in completing tasks. It may be difficult for a sighted designer to understand how blind people mentally represent their environment or how they apply alternative options in accomplishing a task. Designers have responded to these challenges by developing alternative modes of interaction, including audible screen readers,11 external memory aids for exploring haptic graphs,20 non-speech sounds for navigating hypermedia,16 two-finger haptic interfaces for touching virtual objects,22 haptic modeling of virtual objects,13 and multimodal (auditory, haptic, visual) feedback for simple computer-based tasks.10 The effective- ness of these alternative modes of in- teraction is studied primarily through a usability framework, where blind and visually impaired users interact with specific devices in a controlled labo- ratory environment. These develop- ments in assistive technology make a point to take advantage of the alterna- tive modes of interaction available to blind users.
Anirban Bhattacharya - One of the best experts on this subject based on the ideXlab platform.
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Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors
Statistics and Computing, 2020Co-Authors: Pallavi Ray, Debdeep Pati, Anirban BhattacharyaAbstract:This article revisits the problem of Bayesian shape-restricted inference in the light of a recently developed approximate Gaussian process that admits an equivalent formulation of the shape constraints in terms of the basis coefficients. We propose a strategy to efficiently sample from the resulting constrained posterior by absorbing a smooth relaxation of the constraint in the likelihood and using circulant embedding techniques to sample from the unconstrained modified prior . We additionally Pay Careful Attention to mitigate the computational complexity arising from updating hyperparameters within the covariance kernel of the Gaussian process. The developed algorithm is shown to be accurate and highly efficient in simulated and real data examples.
E. Klavins - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Automatic synthesis of controllers for distributed assembly and formation forming
Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002Co-Authors: E. KlavinsAbstract:We consider the task of assembling a large number of self controlled parts (or robots) into copies of a prescribed assembly (or formation). In particular, we introduce a way to synthesize, from a specification of the desired assembly, local controllers to be used by each part which, when taken together, have the global effect of assembling the parts. We Pay Careful Attention to the time and space complexity of the synthesis procedure, showing that the size of the representation of the synthesized controller is polynomial in the size of the specification and that the computational power needed by the controller is low.
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Automatic synthesis of controllers for distributed assembly and formation forming
Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002Co-Authors: E. KlavinsAbstract:We consider the task of assembling a large number of self controlled parts (or robots) into copies of a prescribed assembly (or formation). In particular, we introduce a way to synthesize, from a specification of the desired assembly, local controllers to be used by each part which, when taken together, have the global effect of assembling the parts. We Pay Careful Attention to the time and space complexity of the synthesis procedure, showing that the size of the representation of the synthesized controller is polynomial in the size of the specification and that the computational power needed by the controller is low.
Brian Mcfee - One of the best experts on this subject based on the ideXlab platform.
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Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research
IEEE Signal Processing Magazine, 2019Co-Authors: Brian Mcfee, Mark Cartwright, Justin Salamon, Rachel M. Bittner, Juan Pablo BelloAbstract:In the early years of music information retrieval (MIR), research problems were often centered around conceptually simple tasks, and methods were evaluated on small, idealized data sets. A canonical example of this is genre recognition-i.e., Which one of n genres describes this song?-which was often evaluated on the GTZAN data set (1,000 musical excerpts balanced across ten genres) [1]. As task definitions were simple, so too were signal analysis pipelines, which often derived from methods for speech processing and recognition and typically consisted of simple methods for feature extraction, statistical modeling, and evaluation. When describing a research system, the expected level of detail was superficial: it was sufficient to state, e.g., the number of mel-frequency cepstral coefficients used, the statistical model (e.g., a Gaussian mixture model), the choice of data set, and the evaluation criteria, without stating the underlying software dependencies or implementation details. Because of an increased abundance of methods, the proliferation of software toolkits, the explosion of machine learning, and a focus shift toward more realistic problem settings, modern research systems are substantially more complex than their predecessors. Modern MIR researchers must Pay Careful Attention to detail when processing metadata, implementing evaluation criteria, and disseminating results.