707,124 research outputs found
Natural Language, Mixed-Initiative Personal Assistant Agents
The increasing popularity and use of personal voice assistant technologies, such as Siri and Google Now, is driving and expanding progress toward the long-term and lofty goal of using artificial intelligence to build human-computer dialog systems capable of understanding natural language. While dialog-based systems such as Siri support utterances communicated through natural language, they are limited in the flexibility they afford to the user in interacting with the system and, thus, support primarily action-requesting and information-seeking tasks. Mixed-initiative interaction, on the other hand, is a flexible interaction technique where the user and the system act as equal participants in an activity, and is often exhibited in human-human conversations. In this paper, we study user support for mixed-initiative interaction with dialog-based systems through natural language using a bag-of-words model and k-nearest-neighbor classifier. We study this problem in the context of a toolkit we developed for automated, mixed-initiative dialog system construction, involving a dialog authoring notation and management engine based on lambda calculus, for specifying and implementing task-based, mixed-initiative dialogs. We use ordering at Subway through natural language, human-computer dialogs as a case study. Our results demonstrate that the dialogs authored with our toolkit support the end user\u27s completion of a natural language, human-computer dialog in a mixed-initiative fashion. The use of natural language in the resulting mixed-initiative dialogs afford the user the ability to experience multiple self-directed paths through the dialog and makes the flexibility in communicating user utterances commensurate with that in dialog completion paths---an aspect missing from commercial assistants like Siri
Apps-based Machine Translation on Smart Media Devices - A Review
Machine Translation Systems are part of Natural Language Processing (NLP) that makes communication possible among people using their own native language through computer and smart media devices. This paper describes recent progress in language dictionaries and machine translation commonly used for communications and social interaction among people or Internet users worldwide who speak different languages. Problems of accuracy and quality related to computer translation systems encountered in web & Apps-based translation are described and discussed. Possible programming solutions to the problems are also put forward to create software tools that are able to analyze and synthesize language intelligently based on semantic representation of sentences and phrases. Challenges and problems on Apps-based machine translation on smart devices towards AI, NLP, smart learning and understanding still remain until now, and need to be addressed and solved through collaboration between computational linguists and computer scientists
Optimisation using Natural Language Processing: Personalized Tour Recommendation for Museums
This paper proposes a new method to provide personalized tour recommendation
for museum visits. It combines an optimization of preference criteria of
visitors with an automatic extraction of artwork importance from museum
information based on Natural Language Processing using textual energy. This
project includes researchers from computer and social sciences. Some results
are obtained with numerical experiments. They show that our model clearly
improves the satisfaction of the visitor who follows the proposed tour. This
work foreshadows some interesting outcomes and applications about on-demand
personalized visit of museums in a very near future.Comment: 8 pages, 4 figures; Proceedings of the 2014 Federated Conference on
Computer Science and Information Systems pp. 439-44
A Simplified Overview of Text-To-Speech Synthesis
Computer-based Text-To-Speech systems render text into an audible form, with the aim of sounding as natural as possible. This paper seeks to explain Text-To-Speech synthesis in a simplified manner. Emphasis is placed on the Natural Language Processing (NLP) and Digital Signal Processing (DSP) components of Text-To-Speech Systems. Applications and limitations of speech synthesis are also explore
Tailored Patient Information: Some Issues and Questions
Tailored patient information (TPI) systems are computer programs which
produce personalised heath-information material for patients. TPI systems are
of growing interest to the natural-language generation (NLG) community; many
TPI systems have also been developed in the medical community, usually with
mail-merge technology. No matter what technology is used, experience shows that
it is not easy to field a TPI system, even if it is shown to be effective in
clinical trials. In this paper we discuss some of the difficulties in fielding
TPI systems. This is based on our experiences with 2 TPI systems, one for
generating asthma-information booklets and one for generating smoking-cessation
letters.Comment: This is a paper about technology-transfer. It does not have much
technical conten
Compiling gate networks on an Ising quantum computer
Here we describe a simple mechanical procedure for compiling a quantum gate
network into the natural gates (pulses and delays) for an Ising quantum
computer. The aim is not necessarily to generate the most efficient pulse
sequence, but rather to develop an efficient compilation algorithm that can be
easily implemented in large spin systems. The key observation is that it is not
always necessary to refocus all the undesired couplings in a spin system.
Instead the coupling evolution can simply be tracked and then corrected at some
later time. Although described within the language of NMR the algorithm is
applicable to any design of quantum computer based on Ising couplings.Comment: 5 pages RevTeX4 including 4 figures. Will submit to PR
NaDeA: A Natural Deduction Assistant with a Formalization in Isabelle
We present a new software tool for teaching logic based on natural deduction.
Its proof system is formalized in the proof assistant Isabelle such that its
definition is very precise. Soundness of the formalization has been proved in
Isabelle. The tool is open source software developed in TypeScript / JavaScript
and can thus be used directly in a browser without any further installation.
Although developed for undergraduate computer science students who are used to
study and program concrete computer code in a programming language we consider
the approach relevant for a broader audience and for other proof systems as
well.Comment: Proceedings of the Fourth International Conference on Tools for
Teaching Logic (TTL2015), Rennes, France, June 9-12, 2015. Editors: M.
Antonia Huertas, Jo\~ao Marcos, Mar\'ia Manzano, Sophie Pinchinat,
Fran\c{c}ois Schwarzentrube
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