55,656 research outputs found
Parsing of Spoken Language under Time Constraints
Spoken language applications in natural dialogue settings place serious
requirements on the choice of processing architecture. Especially under adverse
phonetic and acoustic conditions parsing procedures have to be developed which
do not only analyse the incoming speech in a time-synchroneous and incremental
manner, but which are able to schedule their resources according to the varying
conditions of the recognition process. Depending on the actual degree of local
ambiguity the parser has to select among the available constraints in order to
narrow down the search space with as little effort as possible.
A parsing approach based on constraint satisfaction techniques is discussed.
It provides important characteristics of the desired real-time behaviour and
attempts to mimic some of the attention focussing capabilities of the human
speech comprehension mechanism.Comment: 19 pages, LaTe
The Complexity of Rooted Phylogeny Problems
Several computational problems in phylogenetic reconstruction can be
formulated as restrictions of the following general problem: given a formula in
conjunctive normal form where the literals are rooted triples, is there a
rooted binary tree that satisfies the formula? If the formulas do not contain
disjunctions, the problem becomes the famous rooted triple consistency problem,
which can be solved in polynomial time by an algorithm of Aho, Sagiv,
Szymanski, and Ullman. If the clauses in the formulas are restricted to
disjunctions of negated triples, Ng, Steel, and Wormald showed that the problem
remains NP-complete. We systematically study the computational complexity of
the problem for all such restrictions of the clauses in the input formula. For
certain restricted disjunctions of triples we present an algorithm that has
sub-quadratic running time and is asymptotically as fast as the fastest known
algorithm for the rooted triple consistency problem. We also show that any
restriction of the general rooted phylogeny problem that does not fall into our
tractable class is NP-complete, using known results about the complexity of
Boolean constraint satisfaction problems. Finally, we present a pebble game
argument that shows that the rooted triple consistency problem (and also all
generalizations studied in this paper) cannot be solved by Datalog
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A survey of induction algorithms for machine learning
Central to all systems for machine learning from examples is an induction algorithm. The purpose of the algorithm is to generalize from a finite set of training examples a description consistent with the examples seen, and, hopefully, with the potentially infinite set of examples not seen. This paper surveys four machine learning induction algorithms. The knowledge representation schemes and a PDL description of algorithm control are emphasized. System characteristics that are peculiar to a domain of application are de-emphasized. Finally, a comparative summary of the learning algorithms is presented
Description Theory, LTAGs and Underspecified Semantics
An attractive way to model
the relation between an underspecified syntactic representation and
its completions is to let the underspecified representation correspond
to a logical description and the completions to the
models of that description. This approach, which underlies the
Description Theory of (Marcus et al. 1983) has been integrated
in (Vijay-Shanker 1992) with a pure unification approach to
Lexicalized Tree-Adjoining
Grammars (Joshi et al.\ 1975, Schabes 1990). We generalize
Description Theory by integrating semantic
information, that is, we propose to tackle both syntactic and
semantic underspecification using descriptions
Vagueness and referential ambiguity in a large-scale annotated corpus
In this paper, we argue that difficulties in the definition of coreference itself contribute to lower inter-annotator agreement in certain cases. Data from a large referentially annotated corpus serves to corroborate this point, using a quantitative investigation to assess which effects or problems are likely to be the most prominent. Several examples where such problems occur are discussed in more detail, and we then propose a generalisation of Poesio, Reyle and Stevensonās Justified Sloppiness Hypothesis to provide a unified model for these cases of disagreement and argue that a deeper understanding of the phenomena involved allows to tackle problematic cases in a more principled fashion than would be possible using only pre-theoretic intuitions
Trading inference effort versus size in CNF Knowledge Compilation
Knowledge Compilation (KC) studies compilation of boolean functions f into
some formalism F, which allows to answer all queries of a certain kind in
polynomial time. Due to its relevance for SAT solving, we concentrate on the
query type "clausal entailment" (CE), i.e., whether a clause C follows from f
or not, and we consider subclasses of CNF, i.e., clause-sets F with special
properties. In this report we do not allow auxiliary variables (except of the
Outlook), and thus F needs to be equivalent to f.
We consider the hierarchies UC_k <= WC_k, which were introduced by the
authors in 2012. Each level allows CE queries. The first two levels are
well-known classes for KC. Namely UC_0 = WC_0 is the same as PI as studied in
KC, that is, f is represented by the set of all prime implicates, while UC_1 =
WC_1 is the same as UC, the class of unit-refutation complete clause-sets
introduced by del Val 1994. We show that for each k there are (sequences of)
boolean functions with polysize representations in UC_{k+1}, but with an
exponential lower bound on representations in WC_k. Such a separation was
previously only know for k=0. We also consider PC < UC, the class of
propagation-complete clause-sets. We show that there are (sequences of) boolean
functions with polysize representations in UC, while there is an exponential
lower bound for representations in PC. These separations are steps towards a
general conjecture determining the representation power of the hierarchies PC_k
< UC_k <= WC_k. The strong form of this conjecture also allows auxiliary
variables, as discussed in depth in the Outlook.Comment: 43 pages, second version with literature updates. Proceeds with the
separation results from the discontinued arXiv:1302.442
The Virtual Storyteller: story generation by simulation
The Virtual Storyteller is a multi-agent framework that generates stories based on a concept called emergent narrative. In this paper, we describe the motivation and approach of the Virtual Storyteller, and give an overview of the computational processes involved in the story generation process. We also discuss some of the challenges posed by our chosen approach
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