The Turing Test of 1991

1992 ◽  
Vol 36 (4) ◽  
pp. 438-442
Author(s):  
H. McIlvaine Parsons
Keyword(s):  
Human Factors ◽  
Language Processing ◽  
Computer Programs ◽  
Turing Test ◽  
Cognitive Tasks ◽  
First Year ◽  
Human Participants

Interactive computer programs and human participants competed in a Turing Test at the Boston Computer Museum last November in the first year of a competition to determine, ultimately, whether such programs can be indistinguishable from humans in dialogues. The test is named for the British mathematician and computer pioneer who proposed it in 1950. This paper describes the competition, its preparation, and problems which await resolution in future Turing Tests that may culminate in a $100,000 award. The 1991 test was “restricted” in its rules and procedures lest a full test disadvantage the computer programs too severely. The contest posed issues concerning dialogue domains, language processing, inclusion of cognitive tasks, and other features. Since a Turing Test could be interpreted as involving “thinking” and “intelligence” (though Turing had little use for such terms), future tests should intrigue human factors.

A WORD-BASED CHINESE LANGUAGE UNDERSTANDING SYSTEM

1988 ◽  
Vol 02 (01) ◽  
pp. 25-35
Author(s):  
TIAN-SHUN YAO
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Chinese Language ◽  
Computer Programs ◽  
World Knowledge ◽  
Knowledge Source ◽  
Language Understanding ◽  
Language Analysis ◽  
The World

With the word-based theory of natural language processing, a word-based Chinese language understanding system has been developed. In the light of psychological language analysis and the features of the Chinese language, this theory of natural language processing is presented with the description of the computer programs based on it. The heart of the system is to define a Total Information Dictionary and the World Knowledge Source used in the system. The purpose of this research is to develop a system which can understand not only Chinese sentences but also the whole text.

scholarly journals From SARS to COVID-19: A Bibliometric study on Emerging Infectious Diseases with Natural Language Processing technologies

2020 ◽  
Author(s):  
Yinjun Hu ◽  
Mengmeng Chen ◽  
Qian Wang ◽  
Yue Zhu ◽  
Bei Wang ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
International Collaboration ◽  
Citation Impact ◽  
Policy Decision ◽  
Research Quality ◽  
First Year ◽  
Asian Countries ◽  
Processing Technologies

Abstract [Background] On January 7, 2020, the novel coronavirus named "COVID-19" aroused worldwide concern was identified by Chinese scientists. Many related research works were developed for the emerging, rapidly evolving situation of this epidemic. This study aimed to analyze the research literatures on SARS, MERS and COVID-19 to retrieve important information for virologists, epidemiologist and policy decision makers. [Methods] In this study, we collected data from multi data sources and compared bibliometrics indices among COVID-19, Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) up to March 25, 2020. In purpose to extract data in corresponding quantity and scale, the volume of search results will be balance with the limitation of publication years. For further analysis, we extracted 1,480 documents from 1,671 candidates with Natural Language Processing technologies. [Results] In total, 13,945 research literatures of 7 datasets were selected for analysis. Unlike other topics, research passion on epidemic may reach its peak at the first year the outbreak happens. The document type distribution of SARS, MERS and COVID-19 are nearly the same (less than 6 point difference for each type), however, there were notable growth in the research qualities during these three epidemics (3.68, 6.63 and 11.35 for Field-Weighted Citation Impact scores). Asian countries has less international collaboration (less than 35.1\%) than the Occident (more than 49.5\%), which should be noticed as same as research itself. [Conclusions] We found that research passion on epidemics may always reach its peak at the first year after outburst, however, the peak of research on MERS appeared at the third year because of its outburst of reproduction in 2015. For the research quality, although we did better in research qualities than before especially on COVID-19, research on epidemics not started from our own country should not be looked down. Another important effective strategy for enhancing epidemic prevention for China and other Asian countries is to continue strengthening international collaboration.

scholarly journals Demystifying the Vetting Process of Voice-controlled Skills on Markets

2021 ◽  
Vol 5 (3) ◽  
pp. 1-28
Author(s):  
Dawei Wang ◽  
Kai Chen ◽  
Wei Wang
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Turing Test ◽  
Machine Intelligence ◽  
Third Party ◽  
Security And Privacy ◽  
Processing Techniques

Smart speakers, such as Google Home and Amazon Echo, have become popular. They execute user voice commands via their built-in functionalities together with various third-party voice-controlled applications, called skills. Malicious skills have brought significant threats to users in terms of security and privacy. As a countermeasure, only skills passing the strict vetting process can be released onto markets. However, malicious skills have been reported to exist on markets, indicating that the vetting process can be bypassed. This paper aims to demystify the vetting process of skills on main markets to discover weaknesses and protect markets better. To probe the vetting process, we carefully design numerous skills, perform the Turing test, a test for machine intelligence, to determine whether humans or machines perform vetting, and leverage natural language processing techniques to analyze their behaviors. Based on our comprehensive experiments, we gain a good understanding of the vetting process (e.g., machine or human testers and skill exploration strategies) and discover some weaknesses. In this paper, we design three types of attacks to verify our results and prove an attacker can embed sensitive behaviors in skills and bypass the strict vetting process. Accordingly, we also propose countermeasures to these attacks and weaknesses.

scholarly journals Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing

2019 ◽  
Author(s):  
Daniel Sharoh ◽  
Tim van Mourik ◽  
Lauren J. Bains ◽  
Katrien Segaert ◽  
Kirsten Weber ◽  
...  
Keyword(s):  
Language Processing ◽  
Word Reading ◽  
Distributed Networks ◽  
Cognitive Tasks ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Top Down ◽  
Noninvasive Technique ◽  
Whole Brain ◽  
Critical Regions

AbstractLaminar resolution, functional magnetic resonance imaging (lfMRI) is a noninvasive technique with the potential to distinguish top-down and bottom-up signal contributions on the basis of laminar specific interactions between distal regions. Hitherto, lfMRI could not be demonstrated for either whole-brain distributed networks or for complex cognitive tasks. We show that lfMRI can reveal whole-brain directed networks during word reading. We identify distinct, language critical regions based on their association with the top-down signal stream and establish lfMRI for the noninvasive assessment of directed connectivity during task performance.

scholarly journals Grammatical category and the neural processing of phrases

2020 ◽  
Author(s):  
Amelia Burroughs ◽  
Nina Kazanina ◽  
Conor Houghton
Keyword(s):  
Language Processing ◽  
Semantic Processing ◽  
Grammatical Category ◽  
Hierarchical Processing ◽  
Word Level ◽  
Monosyllabic Words ◽  
The Subject ◽  
Cold Food ◽  
Human Participants ◽  
Cortical Entrainment

AbstractThe interlocking roles of lexical, syntactic and semantic processing in language comprehension has been the subject of longstanding debate. Recently, the cortical response to a frequency-tagged linguistic stimulus has been shown to track the rate of phrase and sentence, as well as syllable, presentation. This could be interpreted as evidence for the hierarchical processing of speech, or as a response to the repetition of grammatical category. To examine the extent to which hierarchical structure plays a role in language processing we recorded EEG from human participants as they listen to isochronous streams of monosyllabic words. Comparing responses to sequences in which grammatical category is strictly alternating and chosen such that two-word phrases can be grammatically constructed — cold food loud room — or is absent — rough give ill tell — showed cortical entrainment at the two-word phrase rate was only present in the grammatical condition. Thus, grammatical category repetition alone does not yield entertainment at higher level than a word. On the other hand, cortical entrainment was reduced for the mixed-phrase condition that contained two-word phrases but no grammatical category repetition — that word send less — which is not what would be expected if the measured entrainment reflected purely abstract hierarchical syntactic units. Our results support a model in which word-level grammatical category information is required to build larger units.

scholarly journals Leveraging human knowledge in tabular reinforcement learning: a study of human subjects

2018 ◽  
Vol 33 ◽  
Author(s):  
Ariel Rosenfeld ◽  
Moshe Cohen ◽  
Matthew E. Taylor ◽  
Sarit Kraus
Keyword(s):  
Reinforcement Learning ◽  
Human Factors ◽  
Human Subjects ◽  
Human Study ◽  
Empirical Evaluation ◽  
Similarity Solutions ◽  
Human Knowledge ◽  
State Action ◽  
Reward Shaping ◽  
Human Participants

AbstractReinforcement learning (RL) can be extremely effective in solving complex, real-world problems. However, injecting human knowledge into an RL agent may require extensive effort and expertise on the human designer’s part. To date, human factors are generally not considered in the development and evaluation of possible RL approaches. In this article, we set out to investigate how different methods for injecting human knowledge are applied, in practice, by human designers of varying levels of knowledge and skill. We perform the first empirical evaluation of several methods, including a newly proposed method named State Action Similarity Solutions (SASS) which is based on the notion of similarities in the agent’s state–action space. Through this human study, consisting of 51 human participants, we shed new light on the human factors that play a key role in RL. We find that the classical reward shaping technique seems to be the most natural method for most designers, both expert and non-expert, to speed up RL. However, we further find that our proposed method SASS can be effectively and efficiently combined with reward shaping, and provides a beneficial alternative to using only a single-speedup method with minimal human designer effort overhead.

Human Factors Aspects of Digital Computer Programming for Simulator Control

1965 ◽  
Vol 7 (5) ◽  
pp. 473-482
Author(s):  
Gilbert J. Spesock ◽  
Robert S. Lincoln
Keyword(s):  
Human Factors ◽  
Real Time ◽  
Program Development ◽  
Digital Computer ◽  
Computer Programming ◽  
Computer Programs ◽  
Small Computer ◽  
Simulation Methodology ◽  
Display Control ◽  
Significant Application

Because of the enormous present day effort devoted to the preparation of digital computer programs, special attention should be given to the human factors aspects of program development. Currently available program compilers represent a significant application of certain human factors principles, but are not generally applicable to problems of “real time” programming. Since the creation of appropriate compilers is important to simulation methodology, this report includes a detailed description of a “real time” compiler developed for display/control simulation on a small computer in a human factors laboratory.

Sign in / Sign up

Export Citation Format

Share Document