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The same system used in a validation mode , can be used to check and spot alignment errors in multilingually aligned wordnets as BalkaNet and EuroWordNet . | {
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This paper investigates critical configurations for projective reconstruction from multiple images taken by a camera moving in a straight line . | {
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Projective reconstruction refers to a determination of the 3D geometrical configuration of a set of 3D points and cameras , given only correspondences between points in the images . | {
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Porting a Natural Language Processing -LRB- NLP -RRB- system to a new domain remains one of the bottlenecks in syntactic parsing , because of the amount of effort required to fix gaps in the lexicon , and to attune the existing grammar to the idiosyncracies of the new sublanguage . | {
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This paper shows how the process of fitting a lexicalized grammar to a domain can be automated to a great extent by using a hybrid system that combines traditional knowledge-based techniques with a corpus-based approach . | {
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Unification is often the appropriate method for expressing relations between representations in the form of feature structures ; however , there are circumstances in which a different approach is desirable . | {
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A declarative formalism is presented which permits direct mappings of one feature structure into another , and illustrative examples are given of its application to areas of current interest . | {
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To support engaging human users in robust , mixed-initiative speech dialogue interactions which reach beyond current capabilities in dialogue systems , the DARPA Communicator program -LSB- 1 -RSB- is funding the development of a distributed message-passing infrastructure for dialogue systems which all Communicator part... | {
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We propose a novel limited-memory stochastic block BFGS update for incorporating enriched curvature information in stochastic approximation methods . | {
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In our method , the estimate of the inverse Hessian matrix that is maintained by it , is updated at each iteration using a sketch of the Hessian , i.e. , a randomly generated compressed form of the Hessian . | {
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We propose several sketching strategies , present a new quasi-Newton method that uses stochastic block BFGS updates combined with the variance reduction approach SVRG to compute batch stochastic gradients , and prove linear convergence of the resulting method . | {
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Numerical tests on large-scale logistic regression problems reveal that our method is more robust and substantially outperforms current state-of-the-art methods . | {
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The goal of this research is to develop a spoken language system that will demonstrate the usefulness of voice input for interactive problem solving . | {
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Combining speech recognition and natural language processing to achieve speech understanding , the system will be demonstrated in an application domain relevant to the DoD . | {
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The objective of this project is to develop a robust and high-performance speech recognition system using a segment-based approach to phonetic recognition . | {
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The recognition system will eventually be integrated with natural language processing to achieve spoken language understanding . | {
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Spelling-checkers have become an integral part of most text processing software . | {
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From different reasons among which the speed of processing prevails they are usually based on dictionaries of word forms instead of words . | {
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This approach is sufficient for languages with little inflection such as English , but fails for highly inflective languages such as Czech , Russian , Slovak or other Slavonic languages . | {
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We have developed a special method for describing inflection for the purpose of building spelling-checkers for such languages . | {
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The speed of the resulting program lies somewhere in the middle of the scale of existing spelling-checkers for English and the main dictionary fits into the standard 360K floppy , whereas the number of recognized word forms exceeds 6 million -LRB- for Czech -RRB- . | {
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Further , a special method has been developed for easy word classification . | {
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We present a new HMM tagger that exploits context on both sides of a word to be tagged , and evaluate it in both the unsupervised and supervised case . | {
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Along the way , we present the first comprehensive comparison of unsupervised methods for part-of-speech tagging , noting that published results to date have not been comparable across corpora or lexicons . | {
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Observing that the quality of the lexicon greatly impacts the accuracy that can be achieved by the algorithms , we present a method of HMM training that improves accuracy when training of lexical probabilities is unstable . | {
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Finally , we show how this new tagger achieves state-of-the-art results in a supervised , non-training intensive framework . | {
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We propose a family of non-uniform sampling strategies to provably speed up a class of stochastic optimization algorithms with linear convergence including Stochastic Variance Reduced Gradient -LRB- SVRG -RRB- and Stochastic Dual Coordinate Ascent -LRB- SDCA -RRB- . | {
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For a large family of penalized empirical risk minimization problems , our methods exploit data dependent local smoothness of the loss functions near the optimum , while maintaining convergence guarantees . | {
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Additionally we present algorithms exploiting local smoothness in more aggressive ways , which perform even better in practice . | {
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Statistical language modeling remains a challenging task , in particular for morphologically rich languages . | {
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Recently , new approaches based on factored language models have been developed to address this problem . | {
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These models provide principled ways of including additional conditioning variables other than the preceding words , such as morphological or syntactic features . | {
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This paper presents an entirely data-driven model selection procedure based on genetic search , which is shown to outperform both knowledge-based and random selection procedures on two different language modeling tasks -LRB- Arabic and Turkish -RRB- . | {
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We address appropriate user modeling in order to generate cooperative responses to each user in spoken dialogue systems . | {
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Unlike previous studies that focus on user 's knowledge or typical kinds of users , the user model we propose is more comprehensive . | {
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Moreover , the models are automatically derived by decision tree learning using real dialogue data collected by the system . | {
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Dialogue strategies based on the user modeling are implemented in Kyoto city bus information system that has been developed at our laboratory . | {
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This paper proposes a novel method of building polarity-tagged corpus from HTML documents . | {
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The characteristics of this method is that it is fully automatic and can be applied to arbitrary HTML documents . | {
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The idea behind our method is to utilize certain layout structures and linguistic pattern . | {
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Previous work has used monolingual parallel corpora to extract and generate paraphrases . | {
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We show that this task can be done using bilingual parallel corpora , a much more commonly available resource . | {
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Using alignment techniques from phrase-based statistical machine translation , we show how paraphrases in one language can be identified using a phrase in another language as a pivot . | {
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We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities , and show how it can be refined to take contextual information into account . | {
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We evaluate our paraphrase extraction and ranking methods using a set of manual word alignments , and contrast the quality with paraphrases extracted from automatic alignments . | {
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This paper proposes an automatic , essentially domain-independent means of evaluating Spoken Language Systems -LRB- SLS -RRB- which combines software we have developed for that purpose -LRB- the '' Comparator '' -RRB- and a set of specifications for answer expressions -LRB- the '' Common Answer Specification '' , or CA... | {
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The Common Answer Specification determines the syntax of answer expressions , the minimal content that must be included in them , the data to be included in and excluded from test corpora , and the procedures used by the Comparator . | {
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This paper describes an unsupervised learning method for associative relationships between verb phrases , which is important in developing reliable Q&A systems . | {
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Our aim is to develop an unsupervised learning method that can obtain such an associative relationship , which we call scenario consistency . | {
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The method we are currently working on uses an expectation-maximization -LRB- EM -RRB- based word-clustering algorithm , and we have evaluated the effectiveness of this method using Japanese verb phrases . | {
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We describe the use of text data scraped from the web to augment language models for Automatic Speech Recognition and Keyword Search for Low Resource Languages . | {
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We scrape text from multiple genres including blogs , online news , translated TED talks , and subtitles . | {
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Using linearly interpolated language models , we find that blogs and movie subtitles are more relevant for language modeling of conversational telephone speech and obtain large reductions in out-of-vocabulary keywords . | {
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Furthermore , we show that the web data can improve Term Error Rate Performance by 3.8 % absolute and Maximum Term-Weighted Value in Keyword Search by 0.0076-0 .1059 absolute points . | {
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Pipelined Natural Language Generation -LRB- NLG -RRB- systems have grown increasingly complex as architectural modules were added to support language functionalities such as referring expressions , lexical choice , and revision . | {
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This has given rise to discussions about the relative placement of these new modules in the overall architecture . | {
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We present examples which suggest that in a pipelined NLG architecture , the best approach is to strongly tie it to a revision component . | {
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Finally , we evaluate the approach in a working multi-page system . | {
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In this paper a system which understands and conceptualizes scenes descriptions in natural language is presented . | {
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Specifically , the following components of the system are described : the syntactic analyzer , based on a Procedural Systemic Grammar , the semantic analyzer relying on the Conceptual Dependency Theory , and the dictionary . | {
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The base parser produces a set of candidate parses for each input sentence , with associated probabilities that define an initial ranking of these parses . | {
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A second model then attempts to improve upon this initial ranking , using additional features of the tree as evidence . | {
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},
{
"head": {
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The strength of our approach is that it allows a tree to be represented as an arbitrary set of features , without concerns about how these features interact or overlap and without the need to define a derivation or a generative model which takes these features into account . | {
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} | [] |
We introduce a new method for the reranking task , based on the boosting approach to ranking problems described in Freund et al. -LRB- 1998 -RRB- . | {
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{
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We apply the boosting method to parsing the Wall Street Journal treebank . | {
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{
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The method combined the log-likelihood under a baseline model -LRB- that of Collins -LSB- 1999 -RSB- -RRB- with evidence from an additional 500,000 features over parse trees that were not included in the original model . | {
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The new model achieved 89.75 % F-measure , a 13 % relative decrease in F-measure error over the baseline model 's score of 88.2 % . | {
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... | [] |
The article also introduces a new algorithm for the boosting approach which takes advantage of the sparsity of the feature space in the parsing data . | {
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{
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Experiments show significant efficiency gains for the new algorithm over the obvious implementation of the boosting approach . | {
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We argue that the method is an appealing alternative - in terms of both simplicity and efficiency - to work on feature selection methods within log-linear -LRB- maximum-entropy -RRB- models . | {
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... | [] |
Although the experiments in this article are on natural language parsing -LRB- NLP -RRB- , the approach should be applicable to many other NLP problems which are naturally framed as ranking tasks , for example , speech recognition , machine translation , or natural language generation . | {
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],
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A model is presented to characterize the class of languages obtained by adding reduplication to context-free languages . | {
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"text": "model",
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"text": "class of languages",
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},
{
"head": {
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The model is a pushdown automaton augmented with the ability to check reduplication by using the stack in a new way . | {
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... | [] |
The class of languages generated is shown to lie strictly between the context-free languages and the indexed languages . | {
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"tail": {
"text": "indexed languages",
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}
]
}
} | [] |
The model appears capable of accommodating the sort of reduplications that have been observed to occur in natural languages , but it excludes many of the unnatural constructions that other formal models have permitted . | {
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}
]
}
} | [] |
We present an image set classification algorithm based on unsupervised clustering of labeled training and unla-beled test data where labels are only used in the stopping criterion . | {
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},
{
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The probability distribution of each class over the set of clusters is used to define a true set based similarity measure . | {
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"tail": {
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"end": 121
}
}
]
}
} | [] |
In each iteration , a proximity matrix is efficiently recomputed to better represent the local subspace structure . | {
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"text": "proximity matrix",
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"end": 38
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"tail": {
"text": "local subspace structure",
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}
}
]
}
} | [] |
Initial clusters capture the global data structure and finer clusters at the later stages capture the subtle class differences not visible at the global scale . | {
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"text": "Initial clusters",
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"tail": {
"text": "global data structure",
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}
},
{
"head": {
"text":... | [] |
Image sets are compactly represented with multiple Grass-mannian manifolds which are subsequently embedded in Euclidean space with the proposed spectral clustering algorithm . | {
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"head": {
"text": "Grass-mannian manifolds",
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},
"tail": {
"text": "Image sets",
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},
{
"head": {
"text": "sp... | [] |
We also propose an efficient eigenvector solver which not only reduces the computational cost of spectral clustering by many folds but also improves the clustering quality and final classification results . | {
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"used for": [
{
"head": {
"text": "eigenvector solver",
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"tail": {
"text": "spectral clustering",
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}
],
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... | [] |
This paper investigates some computational problems associated with probabilistic translation models that have recently been adopted in the literature on machine translation . | {
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"text": "computational problems",
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"tail": {
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}
],
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These models can be viewed as pairs of probabilistic context-free grammars working in a ` synchronous ' way . | {
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"head": {
"text": "probabilistic context-free grammars",
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"text": "models",
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"end": 12
}
}
]
}
} | [] |
Active shape models are a powerful and widely used tool to interpret complex image data . | {
"relations": {
"used for": [
{
"head": {
"text": "Active shape models",
"start": 0,
"end": 19
},
"tail": {
"text": "complex image data",
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"end": 87
}
}
]
}
} | [] |
By building models of shape variation they enable search algorithms to use a pri-ori knowledge in an efficient and gainful way . | {
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"used for": [
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"head": {
"text": "search algorithms",
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},
"tail": {
"text": "models of shape variation",
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}
},
{
"head": {
"... | [] |
However , due to the linearity of PCA , non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably . | {
"relations": {
"feature of": [
{
"head": {
"text": "linearity",
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},
"tail": {
"text": "PCA",
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}
],
"hyponym of": [
{
"head": {
"te... | [] |
Although non-linear extensions of active shape models have been proposed and application specific solutions have been used , they still need a certain amount of user interaction during model building . | {
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"used for": [
{
"head": {
"text": "user interaction",
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},
"tail": {
"text": "non-linear extensions of active shape models",
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}
}
]
}
} | [] |
In particular , we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts , each adequate for linear modeling . | {
"relations": {
"used for": [
{
"head": {
"text": "minimum description length principle",
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"end": 89
},
"tail": {
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}
]
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} | [] |
Which in turn leads to a better model in terms of modes of variations . | {
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"feature of": [
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"head": {
"text": "modes of variations",
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"end": 69
},
"tail": {
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}
}
]
}
} | [] |
The proposed method is evaluated on synthetic data , medical images and hand contours . | {
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"evaluate for": [
{
"head": {
"text": "synthetic data",
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"end": 50
},
"tail": {
"text": "method",
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"end": 19
}
},
{
"head": {
"text": "medical im... | [] |
We describe a set of experiments to explore statistical techniques for ranking and selecting the best translations in a graph of translation hypotheses . | {
"relations": {
"used for": [
{
"head": {
"text": "statistical techniques",
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"end": 66
},
"tail": {
"text": "ranking",
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"end": 78
}
}
]
}
} | [] |
In a previous paper -LRB- Carl , 2007 -RRB- we have described how the hypotheses graph is generated through shallow mapping and permutation rules . | {
"relations": {
"used for": [
{
"head": {
"text": "shallow mapping",
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"end": 123
},
"tail": {
"text": "hypotheses graph",
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"end": 86
}
},
{
"head": {
"text": "p... | [] |
This paper describes a number of methods for elaborating statistical feature functions from some of the vector components . | {
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{
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"text": "methods",
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"end": 40
},
"tail": {
"text": "statistical feature functions",
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"end": 86
}
},
{
"head": {
"text":... | [] |
The feature functions are trained off-line on different types of text and their log-linear combination is then used to retrieve the best M translation paths in the graph . | {
"relations": {
"used for": [
{
"head": {
"text": "log-linear combination",
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"end": 102
},
"tail": {
"text": "translation paths",
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}
}
],
"part of": [
{
... | [] |
We compare two language modelling toolkits , the CMU and the SRI toolkit and arrive at three results : 1 -RRB- word-lemma based feature function models produce better results than token-based models , 2 -RRB- adding a PoS-tag feature function to the word-lemma model improves the output and 3 -RRB- weights for lexical t... | {
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"hyponym of": [
{
"head": {
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},
"tail": {
"text": "language modelling toolkits",
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"end": 42
}
}
],
"compare": [
... | [] |
This paper presents a specialized editor for a highly structured dictionary . | {
"relations": {
"used for": [
{
"head": {
"text": "structured dictionary",
"start": 54,
"end": 75
},
"tail": {
"text": "editor",
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"end": 40
}
}
]
}
} | [] |
The basic goal in building that editor was to provide an adequate tool to help lexicologists produce a valid and coherent dictionary on the basis of a linguistic theory . | {
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{
"head": {
"text": "editor",
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},
"tail": {
"text": "dictionary",
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"end": 132
}
},
{
"head": {
"text": "linguistic theor... | [] |
Existing techniques extract term candidates by looking for internal and contextual information associated with domain specific terms . | {
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"feature of": [
{
"head": {
"text": "domain specific terms",
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"end": 132
},
"tail": {
"text": "internal and contextual information",
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}
}
]
}
} | [] |
This paper presents a novel approach for term extraction based on delimiters which are much more stable and domain independent . | {
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"head": {
"text": "approach",
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"end": 36
},
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},
{
"head": {
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The proposed approach is not as sensitive to term frequency as that of previous works . | {
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"end": 21
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"tail": {
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}
}
]
}
} | [] |
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