140,222 research outputs found
Time and information in perceptual adaptation to speech
Presubmission manuscript and supplementary files (stimuli, stimulus presentation code, data, data analysis code).Perceptual adaptation to a talker enables listeners to efficiently resolve the many-to-many mapping between variable speech acoustics and abstract linguistic representations. However, models of speech perception have not delved into the variety or the quantity of information necessary for successful adaptation, nor how adaptation unfolds over time. In three experiments using speeded classification of spoken words, we explored how the quantity (duration), quality (phonetic detail), and temporal continuity of talker-specific context contribute to facilitating perceptual adaptation to speech. In single- and mixed-talker conditions, listeners identified phonetically-confusable target words in isolation or preceded by carrier phrases of varying lengths and phonetic content, spoken by the same talker as the target word. Word identification was always slower in mixed-talker conditions than single-talker ones. However, interference from talker variability decreased as the duration of preceding speech increased but was not affected by the amount of preceding talker-specific phonetic information. Furthermore, efficiency gains from adaptation depended on temporal continuity between preceding speech and the target word. These results suggest that perceptual adaptation to speech may be understood via models of auditory streaming, where perceptual continuity of an auditory object (e.g., a talker) facilitates allocation of attentional resources, resulting in more efficient perceptual processing.NIH NIDCD (R03DC014045
Big data and the SP theory of intelligence
This article is about how the "SP theory of intelligence" and its realisation
in the "SP machine" may, with advantage, be applied to the management and
analysis of big data. The SP system -- introduced in the article and fully
described elsewhere -- may help to overcome the problem of variety in big data:
it has potential as "a universal framework for the representation and
processing of diverse kinds of knowledge" (UFK), helping to reduce the
diversity of formalisms and formats for knowledge and the different ways in
which they are processed. It has strengths in the unsupervised learning or
discovery of structure in data, in pattern recognition, in the parsing and
production of natural language, in several kinds of reasoning, and more. It
lends itself to the analysis of streaming data, helping to overcome the problem
of velocity in big data. Central in the workings of the system is lossless
compression of information: making big data smaller and reducing problems of
storage and management. There is potential for substantial economies in the
transmission of data, for big cuts in the use of energy in computing, for
faster processing, and for smaller and lighter computers. The system provides a
handle on the problem of veracity in big data, with potential to assist in the
management of errors and uncertainties in data. It lends itself to the
visualisation of knowledge structures and inferential processes. A
high-parallel, open-source version of the SP machine would provide a means for
researchers everywhere to explore what can be done with the system and to
create new versions of it.Comment: Accepted for publication in IEEE Acces
Attention and empirical studies of grammar
How is the generation of a grammatical sentence implemented by the human brain? A starting place for such an inquiry lies in linguistic theory. Unfortunately, linguistic theories illuminate only abstract knowledge representations and do not indicate how these representations interact with cognitive architecture to produce discourse. We examine tightly constrained empirical methods to study how grammar interacts with one part of the cognitive architecture, namely attention. Finally, we show that understanding attention as a neural network can link grammatical choice to underlying brain systems. Overall, our commentary supports a multilevel empirical approach that clarifies and expands the connections between cognitive science and linguistics thus advancing the interdisciplinary agenda outlined by Jackendoff
The Sound Manifesto
Computing practice today depends on visual output to drive almost all user
interaction. Other senses, such as audition, may be totally neglected, or used
tangentially, or used in highly restricted specialized ways. We have excellent
audio rendering through D-A conversion, but we lack rich general facilities for
modeling and manipulating sound comparable in quality and flexibility to
graphics. We need co-ordinated research in several disciplines to improve the
use of sound as an interactive information channel.
Incremental and separate improvements in synthesis, analysis, speech
processing, audiology, acoustics, music, etc. will not alone produce the
radical progress that we seek in sonic practice. We also need to create a new
central topic of study in digital audio research. The new topic will assimilate
the contributions of different disciplines on a common foundation. The key
central concept that we lack is sound as a general-purpose information channel.
We must investigate the structure of this information channel, which is driven
by the co-operative development of auditory perception and physical sound
production. Particular audible encodings, such as speech and music, illuminate
sonic information by example, but they are no more sufficient for a
characterization than typography is sufficient for a characterization of visual
information.Comment: To appear in the conference on Critical Technologies for the Future
of Computing, part of SPIE's International Symposium on Optical Science and
Technology, 30 July to 4 August 2000, San Diego, C
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Visual to auditory silent matching task in adults who do and do not stutter
textThe purpose of the present study was to investigate the role of phonological working memory in adults who do and do not stutter through a visual to auditory silent matching task. This task also explored the possible relationship between auditory processing and its ability to affect performance on the task. Participants were 13 adults who stutter (mean age = 28 years), matched in age, gender, handedness, and education level with 13 adults who do not stutter (mean age = 28 years). For the nonvocal visual to auditory task, participants silently read an initial target nonword and matched that target nonword to four subsequent auditory nonword choices. The participants completed this task for 4- syllable and 7- syllable nonwords (N = 8 per set). Results indicated that adults who stutter were significantly less accurate than adults who do not stutter at both syllable lengths. Our present findings support previous research that suggests less efficient phonological working memory in adults who stutter.Communication Sciences and Disorder
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques
This Working Paper Series entry presents a detailed survey of knowledge based systems. After being in a relatively dormant state for many years, only recently is Artificial Intelligence (AI) - that branch of computer science that attempts to have machines emulate intelligent behavior - accomplishing practical results. Most of these results can be attributed to the design and use of Knowledge-Based Systems, KBSs (or ecpert systems) - problem solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. These systems can act as a consultant for various requirements like medical diagnosis, military threat analysis, project risk assessment, etc. These systems possess knowledge to enable them to make intelligent desisions. They are, however, not meant to replace the human specialists in any particular domain. A critical survey of recent work in interactive KBSs is reported. A case study (MYCIN) of a KBS, a list of existing KBSs, and an introduction to the Japanese Fifth Generation Computer Project are provided as appendices. Finally, an extensive set of KBS-related references is provided at the end of the report
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