42,882 research outputs found
Robust semantic analysis for adaptive speech interfaces
The DUMAS project develops speech-based applications that are adaptable to different users and domains. The paper describes the project's robust semantic analysis strategy, used both in the generic framework for the development of multilingual speech-based dialogue systems which is the main project goal, and in the initial test application, a mobile phone-based e-mail interface
An Empirical Approach to Temporal Reference Resolution
This paper presents the results of an empirical investigation of temporal
reference resolution in scheduling dialogs. The algorithm adopted is primarily
a linear-recency based approach that does not include a model of global focus.
A fully automatic system has been developed and evaluated on unseen test data
with good results. This paper presents the results of an intercoder reliability
study, a model of temporal reference resolution that supports linear recency
and has very good coverage, the results of the system evaluated on unseen test
data, and a detailed analysis of the dialogs assessing the viability of the
approach.Comment: 13 pages, latex using aclap.st
The Many Functions of Discourse Particles: A Computational Model of Pragmatic Interpretation
We present a connectionist model for the interpretation of discourse\ud
particles in real dialogues that is based on neuronal\ud
principles of categorization (categorical perception, prototype\ud
formation, contextual interpretation). It can be shown that\ud
discourse particles operate just like other morphological and\ud
lexical items with respect to interpretation processes. The description\ud
proposed locates discourse particles in an elaborate\ud
model of communication which incorporates many different\ud
aspects of the communicative situation. We therefore also\ud
attempt to explore the content of the category discourse particle.\ud
We present a detailed analysis of the meaning assignment\ud
problem and show that 80%– 90% correctness for unseen discourse\ud
particles can be reached with the feature analysis provided.\ud
Furthermore, we show that ‘analogical transfer’ from\ud
one discourse particle to another is facilitated if prototypes\ud
are computed and used as the basis for generalization. We\ud
conclude that the interpretation processes which are a part of\ud
the human cognitive system are very similar with respect to\ud
different linguistic items. However, the analysis of discourse\ud
particles shows clearly that any explanatory theory of language\ud
needs to incorporate a theory of communication processes
Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction
We develop a natural language interface for human robot interaction that
implements reasoning about deep semantics in natural language. To realize the
required deep analysis, we employ methods from cognitive linguistics, namely
the modular and compositional framework of Embodied Construction Grammar (ECG)
[Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference
resolution problems and other issues related to deep semantics and
compositionality of natural language. This also includes verbal interaction
with humans to clarify commands and queries that are too ambiguous to be
executed safely. We implement our NLU framework as a ROS package and present
proof-of-concept scenarios with different robots, as well as a survey on the
state of the art
Efficient deep processing of japanese
We present a broad coverage Japanese grammar written in the HPSG formalism with MRS semantics. The grammar is created for use in real world applications, such that robustness and performance issues play an important role. It is connected to a POS tagging and word segmentation tool. This grammar is being developed in a multilingual context, requiring MRS structures that are easily comparable across languages
Robust Grammatical Analysis for Spoken Dialogue Systems
We argue that grammatical analysis is a viable alternative to concept
spotting for processing spoken input in a practical spoken dialogue system. We
discuss the structure of the grammar, and a model for robust parsing which
combines linguistic sources of information and statistical sources of
information. We discuss test results suggesting that grammatical processing
allows fast and accurate processing of spoken input.Comment: Accepted for JNL
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