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Consequently , the proposed approach can be applied to different domains easily and it is especially useful for resource-limited domains . | {
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Evaluations conducted on two different domains for Chinese term extraction show significant improvements over existing techniques which verifies its efficiency and domain independent nature . | {
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Experiments on new term extraction indicate that the proposed approach can also serve as an effective tool for domain lexicon expansion . | {
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We describe a method for identifying systematic patterns in translation data using part-of-speech tag sequences . | {
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We incorporate this analysis into a diagnostic tool intended for developers of machine translation systems , and demonstrate how our application can be used by developers to explore patterns in machine translation output . | {
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We study the number of hidden layers required by a multilayer neu-ral network with threshold units to compute a function f from n d to -LCB- O , I -RCB- . | {
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We show that adding these conditions to Gib-son 's assumptions is not sufficient to ensure global computability with one hidden layer , by exhibiting a new non-local configuration , the `` critical cycle '' , which implies that f is not computable with one hidden layer . | {
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This paper presents an approach to estimate the intrinsic texture properties -LRB- albedo , shading , normal -RRB- of scenes from multiple view acquisition under unknown illumination conditions . | {
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Unlike previous video relighting methods , the approach does not assume regions of uniform albedo , which makes it applicable to richly textured scenes . | {
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We show that intrinsic image methods can be used to refine an initial , low-frequency shading estimate based on a global lighting reconstruction from an original texture and coarse scene geometry in order to resolve the inherent global ambiguity in shading . | {
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The method is applied to relight-ing of free-viewpoint rendering from multiple view video capture . | {
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This demonstrates relighting with reproduction of fine surface detail . | {
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Following recent developments in the automatic evaluation of machine translation and document summarization , we present a similar approach , implemented in a measure called POURPRE , for automatically evaluating answers to definition questions . | {
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Experiments with the TREC 2003 and TREC 2004 QA tracks indicate that rankings produced by our metric correlate highly with official rankings , and that POURPRE outperforms direct application of existing metrics . | {
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Recent advances in Automatic Speech Recognition technology have put the goal of naturally sounding dialog systems within reach . | {
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The issue of system response to users has been extensively studied by the natural language generation community , though rarely in the context of dialog systems . | {
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We show how research in generation can be adapted to dialog systems , and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employing machine learning techniques . | {
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We present a tool , called ILIMP , which takes as input a raw text in French and produces as output the same text in which every occurrence of the pronoun il is tagged either with tag -LSB- ANA -RSB- for anaphoric or -LSB- IMP -RSB- for impersonal or expletive . | {
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This tool is therefore designed to distinguish between the anaphoric occurrences of il , for which an anaphora resolution system has to look for an antecedent , and the expletive occurrences of this pronoun , for which it does not make sense to look for an antecedent . | {
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The precision rate for ILIMP is 97,5 % . | {
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Other tasks using the method developed for ILIMP are described briefly , as well as the use of ILIMP in a modular syntactic analysis system . | {
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Little is thus known about the robustness of speech cues in the wild . | {
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This study compares the effect of noise and reverberation on depression prediction using 1 -RRB- standard mel-frequency cepstral coefficients -LRB- MFCCs -RRB- , and 2 -RRB- features designed for noise robustness , damped oscillator cepstral coefficients -LRB- DOCCs -RRB- . | {
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Results using additive noise and reverberation reveal a consistent pattern of findings for multiple evaluation metrics under both matched and mismatched conditions . | {
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First and most notably : standard MFCC features suffer dramatically under test/train mismatch for both noise and reverberation ; DOCC features are far more robust . | {
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Third , artificial neural networks tend to outperform support vector regression . | {
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Fourth , spontaneous speech appears to offer better robustness than read speech . | {
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Finally , a cross-corpus -LRB- and cross-language -RRB- experiment reveals better noise and reverberation robustness for DOCCs than for MFCCs . | {
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This paper proposes document oriented preference sets -LRB- DoPS -RRB- for the disambiguation of the dependency structure of sentences . | {
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Sentence ambiguities can be resolved by using domain targeted preference knowledge without using complicated large knowledgebases . | {
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Implementation and empirical results are described for the the analysis of dependency structures of Japanese patent claim sentences . | {
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Multimodal interfaces require effective parsing and understanding of utterances whose content is distributed across multiple input modes . | {
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Johnston 1998 presents an approach in which strategies for multimodal integration are stated declaratively using a unification-based grammar that is used by a multidimensional chart parser to compose inputs . | {
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In this paper , we present an alternative approach in which multimodal parsing and understanding are achieved using a weighted finite-state device which takes speech and gesture streams as inputs and outputs their joint interpretation . | {
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This approach is significantly more efficient , enables tight-coupling of multimodal understanding with speech recognition , and provides a general probabilistic framework for multimodal ambiguity resolution . | {
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Recently , we initiated a project to develop a phonetically-based spoken language understanding system called SUMMIT . | {
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In contrast to many of the past efforts that make use of heuristic rules whose development requires intense knowledge engineering , our approach attempts to express the speech knowledge within a formal framework using well-defined mathematical tools . | {
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In our system , features and decision strategies are discovered and trained automatically , using a large body of speech data . | {
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This paper describes an implemented program that takes a tagged text corpus and generates a partial list of the subcategorization frames in which each verb occurs . | {
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We present a method for estimating the relative pose of two calibrated or uncalibrated non-overlapping surveillance cameras from observing a moving object . | {
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We show how to tackle the problem of missing point correspondences heavily required by SfM pipelines and how to go beyond this basic paradigm . | {
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We relax the non-linear nature of the problem by accepting two assumptions which surveillance scenarios offer , ie . | {
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By those assumptions we cast the problem as a Quadratic Eigenvalue Problem offering an elegant way of treating nonlinear monomials and delivering a quasi closed-form solution as a reliable starting point for a further bundle adjustment . | {
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We are the first to bring the closed form solution to such a very practical problem arising in video surveillance . | {
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In this paper , we propose a human action recognition system suitable for embedded computer vision applications in security systems , human-computer interaction and intelligent environments . | {
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Our system is suitable for embedded computer vision application based on three reasons . | {
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Firstly , the system was based on a linear Support Vector Machine -LRB- SVM -RRB- classifier where classification progress can be implemented easily and quickly in embedded hardware . | {
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Secondly , we use compacted motion features easily obtained from videos . | {
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We address the limitations of the well known Motion History Image -LRB- MHI -RRB- and propose a new Hierarchical Motion History Histogram -LRB- HMHH -RRB- feature to represent the motion information . | {
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HMHH not only provides rich motion information , but also remains computationally inexpensive . | {
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Finally , we combine MHI and HMHH together and extract a low dimension feature vector to be used in the SVM classifiers . | {
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Experimental results show that our system achieves significant improvement on the recognition performance . | {
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In this paper I will argue for a model of grammatical processing that is based on uniform processing and knowledge sources . | {
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The main feature of this model is to view parsing and generation as two strongly interleaved tasks performed by a single parametrized deduction process . | {
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Link detection has been regarded as a core technology for the Topic Detection and Tracking tasks of new event detection . | {
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In this paper we formulate story link detection and new event detection as information retrieval task and hypothesize on the impact of precision and recall on both systems . | {
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Motivated by these arguments , we introduce a number of new performance enhancing techniques including part of speech tagging , new similarity measures and expanded stop lists . | {
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We attempt to understand visual classification in humans using both psy-chophysical and machine learning techniques . | {
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Frontal views of human faces were used for a gender classification task . | {
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Several hyperplane learning algorithms were used on the same classification task using the Principal Components of the texture and flowfield representation of the faces . | {
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The classification performance of the learning algorithms was estimated using the face database with the true gender of the faces as labels , and also with the gender estimated by the subjects . | {
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Our results suggest that human classification can be modeled by some hyperplane algorithms in the feature space we used . | {
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... | [] |
For classification , the brain needs more processing for stimuli close to that hyperplane than for those further away . | {
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} | [] |
In this paper , we present a corpus-based supervised word sense disambiguation -LRB- WSD -RRB- system for Dutch which combines statistical classification -LRB- maximum entropy -RRB- with linguistic information . | {
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"text": "Dutch",
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... | [] |
Instead of building individual classifiers per ambiguous wordform , we introduce a lemma-based approach . | {
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The advantage of this novel method is that it clusters all inflected forms of an ambiguous word in one classifier , therefore augmenting the training material available to the algorithm . | {
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Testing the lemma-based model on the Dutch Senseval-2 test data , we achieve a significant increase in accuracy over the wordform model . | {
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We propose an exact , general and efficient coarse-to-fine energy minimization strategy for semantic video segmenta-tion . | {
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... | [] |
Our strategy is based on a hierarchical abstraction of the supervoxel graph that allows us to minimize an energy defined at the finest level of the hierarchy by minimizing a series of simpler energies defined over coarser graphs . | {
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It is general , i.e. , it can be used to minimize any energy function -LRB- e.g. , unary , pairwise , and higher-order terms -RRB- with any existing energy minimization algorithm -LRB- e.g. , graph cuts and belief propagation -RRB- . | {
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{
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It also gives significant speedups in inference for several datasets with varying degrees of spatio-temporal continuity . | {
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We also discuss the strengths and weaknesses of our strategy relative to existing hierarchical approaches , and the kinds of image and video data that provide the best speedups . | {
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} | [] |
Motivated by the success of ensemble methods in machine learning and other areas of natural language processing , we developed a multi-strategy and multi-source approach to question answering which is based on combining the results from different answering agents searching for answers in multiple corpora . | {
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{
"head": {
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The answering agents adopt fundamentally different strategies , one utilizing primarily knowledge-based mechanisms and the other adopting statistical techniques . | {
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{
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We present our multi-level answer resolution algorithm that combines results from the answering agents at the question , passage , and/or answer levels . | {
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} | [] |
Experiments evaluating the effectiveness of our answer resolution algorithm show a 35.0 % relative improvement over our baseline system in the number of questions correctly answered , and a 32.8 % improvement according to the average precision metric . | {
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"compare": [
{
"head": {
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... | [] |
Word Identification has been an important and active issue in Chinese Natural Language Processing . | {
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"hyponym of": [
{
"head": {
"text": "Word Identification",
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"end": 19
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"tail": {
"text": "Chinese Natural Language Processing",
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} | [] |
In this paper , a new mechanism , based on the concept of sublanguage , is proposed for identifying unknown words , especially personal names , in Chinese newspapers . | {
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{
"head": {
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},
{
"head": {
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The proposed mechanism includes title-driven name recognition , adaptive dynamic word formation , identification of 2-character and 3-character Chinese names without title . | {
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"head": {
"text": "title-driven name recognition",
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{
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This report describes Paul , a computer text generation system designed to create cohesive text through the use of lexical substitutions . | {
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"head": {
"text": "Paul",
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"tail": {
"text": "computer text generation system",
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}
],
"used for": [
{
"h... | [] |
Specifically , this system is designed to deterministically choose between pronominalization , superordinate substitution , and definite noun phrase reiteration . | {
"relations": {
"compare": [
{
"head": {
"text": "pronominalization",
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"end": 92
},
"tail": {
"text": "superordinate substitution",
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},
{
"head": {
... | [] |
The system identifies a strength of antecedence recovery for each of the lexical substitutions . | {
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"used for": [
{
"head": {
"text": "system",
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"end": 10
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"text": "antecedence recovery",
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},
{
"head": {
"text": "anteceden... | [] |
It describes the automated training and evaluation of an Optimal Position Policy , a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure . | {
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"used for": [
{
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"text": "method",
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"tail": {
"text": "positions of topic-bearing sentences",
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},
{
"head": {
... | [] |
This method can be used in applications such as information retrieval , routing , and text summarization . | {
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"text": "method",
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],
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{
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... | [] |
We describe a general framework for online multiclass learning based on the notion of hypothesis sharing . | {
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{
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"text": "framework",
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"end": 31
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"text": "online multiclass learning",
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},
{
"head": {
"text": ... | [] |
We generalize the multiclass Perceptron to our framework and derive a unifying mistake bound analysis . | {
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"head": {
"text": "multiclass Perceptron",
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"end": 39
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"tail": {
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"end": 56
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]
}
} | [] |
We demonstrate the merits of our approach by comparing it to previous methods on both synthetic and natural datasets . | {
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"head": {
"text": "it",
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"end": 24
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],
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{
"head": {
"text":... | [] |
We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions . | {
"relations": {
"used for": [
{
"head": {
"text": "supervised machine learning",
"start": 21,
"end": 48
},
"tail": {
"text": "statistical models of WH-questions",
"start": 94,
"end": 128
}
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]
}
} | [] |
These models , which are built from shallow linguistic features of questions , are employed to predict target variables which represent a user 's informational goals . | {
"relations": {
"used for": [
{
"head": {
"text": "shallow linguistic features of questions",
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"end": 76
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"tail": {
"text": "models",
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"end": 12
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]
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} | [] |
We argue in favor of the the use of labeled directed graph to represent various types of linguistic structures , and illustrate how this allows one to view NLP tasks as graph transformations . | {
"relations": {
"used for": [
{
"head": {
"text": "labeled directed graph",
"start": 36,
"end": 58
},
"tail": {
"text": "linguistic structures",
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"end": 110
}
},
{
"head": {
... | [] |
We present a general method for learning such transformations from an annotated corpus and describe experiments with two applications of the method : identification of non-local depenencies -LRB- using Penn Treebank data -RRB- and semantic role labeling -LRB- using Proposition Bank data -RRB- . | {
"relations": {
"used for": [
{
"head": {
"text": "method",
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},
"tail": {
"text": "transformations",
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"end": 61
}
},
{
"head": {
"text": "annotated cor... | [] |
We describe a generative probabilistic model of natural language , which we call HBG , that takes advantage of detailed linguistic information to resolve ambiguity . | {
"relations": {
"used for": [
{
"head": {
"text": "linguistic information",
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"end": 142
},
"tail": {
"text": "ambiguity",
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}
}
]
}
} | [] |
HBG incorporates lexical , syntactic , semantic , and structural information from the parse tree into the disambiguation process in a novel way . | {
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"used for": [
{
"head": {
"text": "HBG",
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"end": 3
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"tail": {
"text": "disambiguation process",
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},
{
"head": {
"text": "lexical ,... | [] |
We use a corpus of bracketed sentences , called a Treebank , in combination with decision tree building to tease out the relevant aspects of a parse tree that will determine the correct parse of a sentence . | {
"relations": {
"conjunction": [
{
"head": {
"text": "corpus of bracketed sentences",
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"tail": {
"text": "decision tree building",
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],
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... | [] |
This stands in contrast to the usual approach of further grammar tailoring via the usual linguistic introspection in the hope of generating the correct parse . | {
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"used for": [
{
"head": {
"text": "grammar tailoring",
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"text": "parse",
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},
{
"head": {
"text": "linguistic... | [] |
In head-to-head tests against one of the best existing robust probabilistic parsing models , which we call P-CFG , the HBG model significantly outperforms P-CFG , increasing the parsing accuracy rate from 60 % to 75 % , a 37 % reduction in error . | {
"relations": {
"hyponym of": [
{
"head": {
"text": "P-CFG",
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"tail": {
"text": "robust probabilistic parsing models",
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"end": 90
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}
],
"compare": [
{
... | [] |
The framework of the analysis is model-theoretic semantics . | {
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"used for": [
{
"head": {
"text": "model-theoretic semantics",
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"end": 58
},
"tail": {
"text": "analysis",
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]
}
} | [] |
This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources . | {
"relations": {
"used for": [
{
"head": {
"text": "machine-readable resources",
"start": 74,
"end": 100
},
"tail": {
"text": "word-sense ambiguity",
"start": 34,
"end": 54
}
},
{
"head": {
... | [] |
We describe two experiments : one which ignored word-sense distinctions , resulting in 6.3 % accuracy for semantic classification of verbs based on -LRB- Levin , 1993 -RRB- ; and one which exploited word-sense distinctions , resulting in 97.9 % accuracy . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "accuracy",
"start": 93,
"end": 101
},
"tail": {
"text": "semantic classification",
"start": 106,
"end": 129
}
}
]
}
} | [] |
These experiments were dual purpose : -LRB- 1 -RRB- to validate the central thesis of the work of -LRB- Levin , 1993 -RRB- , i.e. , that verb semantics and syntactic behavior are predictably related ; -LRB- 2 -RRB- to demonstrate that a 15-fold improvement can be achieved in deriving semantic information from syntactic... | {
"relations": {
"conjunction": [
{
"head": {
"text": "verb semantics",
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},
"tail": {
"text": "syntactic behavior",
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"end": 174
}
}
],
"used for": [
{
... | [] |
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