scholarly journals Real Time Sign Language Processing System

2018 ◽  
Vol 6 (4) ◽  
pp. 2445-2448
Author(s):  
Arfat Shaikh
Keyword(s):  
Real Time ◽  
Sign Language ◽  
Language Processing ◽  
Processing System

scholarly journals Discovering prominence and its role in language processing: An individual (differences) approach

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Phillip M. Alday ◽  
Matthias Schlesewsky ◽  
Ina Bornkessel-Schlesewsky
Keyword(s):  
Individual Differences ◽  
Real Time ◽  
Language Processing ◽  
Language Comprehension ◽  
Processing System ◽  
Partial Ordering ◽  
Human Language ◽  
Qualitative Work ◽  
State Of Affairs ◽  
The Relationship

AbstractIt has been suggested that, during real time language comprehension, the human language processing system attempts to identify the argument primarily responsible for the state of affairs (the “actor”) as quickly and unambiguously as possible. However, previous work on a prominence (e.g. animacy, definiteness, case marking) based heuristic for actor identification has suffered from underspecification of the relationship between different cue hierarchies. Qualitative work has yielded a partial ordering of many features (e.g.: OpenSesame experiment and Python support scripts, sample stimuli, R scripts for analysis

In Search of a Human Language Processing System

1985 ◽  
Vol 30 (7) ◽  
pp. 529-531
Author(s):  
Patrick Carroll
Keyword(s):  
Language Processing ◽  
Processing System ◽  
Human Language

Putting up barriers

2017 ◽  
Author(s):  
David J. Lobina
Keyword(s):  
Knowledge Base ◽  
Real Time ◽  
Language Processing ◽  
Cognitive Domain ◽  
Linguistic Knowledge ◽  
Levels Of Explanation ◽  
Real Time Processing ◽  
Time Processing ◽  
Neural Underpinnings ◽  
Different Levels

The study of cognitive phenomena is best approached in an orderly manner. It must begin with an analysis of the function in intension at the heart of any cognitive domain (its knowledge base), then proceed to the manner in which such knowledge is put into use in real-time processing, concluding with a domain’s neural underpinnings, its development in ontogeny, etc. Such an approach to the study of cognition involves the adoption of different levels of explanation/description, as prescribed by David Marr and many others, each level requiring its own methodology and supplying its own data to be accounted for. The study of recursion in cognition is badly in need of a systematic and well-ordered approach, and this chapter lays out the blueprint to be followed in the book by focusing on a strict separation between how this notion applies in linguistic knowledge and how it manifests itself in language processing.

scholarly journals Limits on expectation-based processing: Use of grammatical aspect for co-reference in L2

2020 ◽  
pp. 1-25
Author(s):  
Theres Grüter ◽  
Hannah Rohde
Keyword(s):  
Real Time ◽  
Language Processing ◽  
Judgment Task ◽  
Linguistic Knowledge ◽  
Real Time Processing ◽  
Time Processing ◽  
Grammatical Aspect ◽  
Level Information ◽  
Native Speakers Of English ◽  
Reference Processing

Abstract This study examines the use of discourse-level information to create expectations about reference in real-time processing, testing whether patterns previously observed among native speakers of English generalize to nonnative speakers. Findings from a visual-world eye-tracking experiment show that native (L1; N = 53) but not nonnative (L2; N = 52) listeners’ proactive coreference expectations are modulated by grammatical aspect in transfer-of-possession events. Results from an offline judgment task show these L2 participants did not differ from L1 speakers in their interpretation of aspect marking on transfer-of-possession predicates in English, indicating it is not lack of linguistic knowledge but utilization of this knowledge in real-time processing that distinguishes the groups. English proficiency, although varying substantially within the L2 group, did not modulate L2 listeners’ use of grammatical aspect for reference processing. These findings contribute to the broader endeavor of delineating the role of prediction in human language processing in general, and in the processing of discourse-level information among L2 users in particular.

What's my App?

2021 ◽  
Vol 48 (4) ◽  
pp. 41-44
Author(s):  
Dena Markudova ◽  
Martino Trevisan ◽  
Paolo Garza ◽  
Michela Meo ◽  
Maurizio M. Munafo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Real Time ◽  
Language Processing ◽  
Traffic Management ◽  
Quality Of Experience ◽  
Broadband Internet ◽  
Management Policies ◽  
Control Traffic

With the spread of broadband Internet, Real-Time Communication (RTC) platforms have become increasingly popular and have transformed the way people communicate. Thus, it is fundamental that the network adopts traffic management policies that ensure appropriate Quality of Experience to users of RTC applications. A key step for this is the identification of the applications behind RTC traffic, which in turn allows to allocate adequate resources and make decisions based on the specific application's requirements. In this paper, we introduce a machine learning-based system for identifying the traffic of RTC applications. It builds on the domains contacted before starting a call and leverages techniques from Natural Language Processing (NLP) to build meaningful features. Our system works in real-time and is robust to the peculiarities of the RTP implementations of different applications, since it uses only control traffic. Experimental results show that our approach classifies 5 well-known meeting applications with an F1 score of 0.89.

scholarly journals A Real Time Processing system for big data in astronomy: Applications to HERA

2021 ◽  
pp. 100489
Author(s):  
Paul La Plante ◽  
P.K.G. Williams ◽  
M. Kolopanis ◽  
J.S. Dillon ◽  
A.P. Beardsley ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Processing System ◽  
Real Time Processing ◽  
Time Processing
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