input stringlengths 37 565 | output dict | schema listlengths 0 0 |
|---|---|---|
Our algorithm reported more than 99 % accuracy in both language identification and key prediction . | {
"relations": {
"used for": [
{
"head": {
"text": "algorithm",
"start": 4,
"end": 13
},
"tail": {
"text": "language identification",
"start": 55,
"end": 78
}
},
{
"head": {
"text": "alg... | [] |
This paper concerns the discourse understanding process in spoken dialogue systems . | {
"relations": {
"used for": [
{
"head": {
"text": "discourse understanding process",
"start": 24,
"end": 55
},
"tail": {
"text": "spoken dialogue systems",
"start": 59,
"end": 82
}
}
]
}
} | [] |
This process enables the system to understand user utterances based on the context of a dialogue . | {
"relations": {
"used for": [
{
"head": {
"text": "system",
"start": 25,
"end": 31
},
"tail": {
"text": "user utterances",
"start": 46,
"end": 61
}
}
]
}
} | [] |
This paper proposes a method for resolving this ambiguity based on statistical information obtained from dialogue corpora . | {
"relations": {
"used for": [
{
"head": {
"text": "method",
"start": 22,
"end": 28
},
"tail": {
"text": "ambiguity",
"start": 48,
"end": 57
}
},
{
"head": {
"text": "statistical informa... | [] |
Unlike conventional methods that use hand-crafted rules , the proposed method enables easy design of the discourse understanding process . | {
"relations": {
"used for": [
{
"head": {
"text": "hand-crafted rules",
"start": 37,
"end": 55
},
"tail": {
"text": "methods",
"start": 20,
"end": 27
}
}
]
}
} | [] |
Experiment results have shown that a system that exploits the proposed method performs sufficiently and that holding multiple candidates for understanding results is effective . | {
"relations": {
"used for": [
{
"head": {
"text": "system",
"start": 37,
"end": 43
},
"tail": {
"text": "method",
"start": 71,
"end": 77
}
}
]
}
} | [] |
We consider the problem of question-focused sentence retrieval from complex news articles describing multi-event stories published over time . | {
"relations": {
"used for": [
{
"head": {
"text": "news articles",
"start": 76,
"end": 89
},
"tail": {
"text": "question-focused sentence retrieval",
"start": 27,
"end": 62
}
}
],
"feature of": [
... | [] |
To address the sentence retrieval problem , we apply a stochastic , graph-based method for comparing the relative importance of the textual units , which was previously used successfully for generic summarization . | {
"relations": {
"used for": [
{
"head": {
"text": "stochastic , graph-based method",
"start": 55,
"end": 86
},
"tail": {
"text": "sentence retrieval problem",
"start": 15,
"end": 41
}
},
{
"head"... | [] |
Currently , we present a topic-sensitive version of our method and hypothesize that it can outperform a competitive baseline , which compares the similarity of each sentence to the input question via IDF-weighted word overlap . | {
"relations": {
"compare": [
{
"head": {
"text": "baseline",
"start": 116,
"end": 124
},
"tail": {
"text": "it",
"start": 35,
"end": 37
}
}
]
}
} | [] |
In our experiments , the method achieves a TRDR score that is significantly higher than that of the baseline . | {
"relations": {
"compare": [
{
"head": {
"text": "method",
"start": 25,
"end": 31
},
"tail": {
"text": "baseline",
"start": 100,
"end": 108
}
}
],
"evaluate for": [
{
"head": {
... | [] |
This paper proposes that sentence analysis should be treated as defeasible reasoning , and presents such a treatment for Japanese sentence analyses using an argumentation system by Konolige , which is a formalization of defeasible reasoning , that includes arguments and defeat rules that capture defeasibility . | {
"relations": {
"used for": [
{
"head": {
"text": "defeasible reasoning",
"start": 64,
"end": 84
},
"tail": {
"text": "sentence analysis",
"start": 25,
"end": 42
}
},
{
"head": {
"text"... | [] |
It gives an overview of methods used for visual speech animation , parameterization of a human face and a tongue , necessary data sources and a synthesis method . | {
"relations": {
"used for": [
{
"head": {
"text": "methods",
"start": 24,
"end": 31
},
"tail": {
"text": "visual speech animation",
"start": 41,
"end": 64
}
}
]
}
} | [] |
A 3D animation model is used for a pseudo-muscular animation schema to create such animation of visual speech which is usable for a lipreading . | {
"relations": {
"used for": [
{
"head": {
"text": "3D animation model",
"start": 2,
"end": 20
},
"tail": {
"text": "pseudo-muscular animation schema",
"start": 35,
"end": 67
}
},
{
"head": {
... | [] |
Furthermore , a problem of forming articulatory trajectories is formulated to solve labial coarticulation effects . | {
"relations": {
"used for": [
{
"head": {
"text": "forming articulatory trajectories",
"start": 27,
"end": 60
},
"tail": {
"text": "labial coarticulation effects",
"start": 84,
"end": 113
}
}
]
}
} | [] |
It is used for the synthesis method based on a selection of articulatory targets and interpolation technique . | {
"relations": {
"used for": [
{
"head": {
"text": "It",
"start": 0,
"end": 2
},
"tail": {
"text": "synthesis method",
"start": 19,
"end": 35
}
},
{
"head": {
"text": "selection of artic... | [] |
However , our experience with TACITUS ; especially in the MUC-3 evaluation , has shown that principled techniques for syntactic and pragmatic analysis can be bolstered with methods for achieving robustness . | {
"relations": {
"used for": [
{
"head": {
"text": "techniques",
"start": 103,
"end": 113
},
"tail": {
"text": "syntactic and pragmatic analysis",
"start": 118,
"end": 150
}
}
],
"evaluate for": [
... | [] |
We describe three techniques for making syntactic analysis more robust -- an agenda-based scheduling parser , a recovery technique for failed parses , and a new technique called terminal substring parsing . | {
"relations": {
"used for": [
{
"head": {
"text": "three techniques",
"start": 12,
"end": 28
},
"tail": {
"text": "syntactic analysis",
"start": 40,
"end": 58
}
},
{
"head": {
"text": "... | [] |
For pragmatics processing , we describe how the method of abductive inference is inherently robust , in that an interpretation is always possible , so that in the absence of the required world knowledge , performance degrades gracefully . | {
"relations": {
"used for": [
{
"head": {
"text": "abductive inference",
"start": 58,
"end": 77
},
"tail": {
"text": "pragmatics processing",
"start": 4,
"end": 25
}
}
]
}
} | [] |
This paper proposes a Hidden Markov Model -LRB- HMM -RRB- and an HMM-based chunk tagger , from which a named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system is built to recognize and classify names , times and numerical quantities . | {
"relations": {
"conjunction": [
{
"head": {
"text": "Hidden Markov Model -LRB- HMM -RRB-",
"start": 22,
"end": 57
},
"tail": {
"text": "HMM-based chunk tagger",
"start": 65,
"end": 87
}
},
{
"he... | [] |
Through the HMM , our system is able to apply and integrate four types of internal and external evidences : 1 -RRB- simple deterministic internal feature of the words , such as capitalization and digitalization ; 2 -RRB- internal semantic feature of important triggers ; 3 -RRB- internal gazetteer feature ; 4 -RRB- exte... | {
"relations": {
"hyponym of": [
{
"head": {
"text": "capitalization",
"start": 177,
"end": 191
},
"tail": {
"text": "deterministic internal feature of the words",
"start": 123,
"end": 166
}
},
{
... | [] |
Evaluation of our system on MUC-6 and MUC-7 English NE tasks achieves F-measures of 96.6 % and 94.1 % respectively . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "MUC-6 and MUC-7 English NE tasks",
"start": 28,
"end": 60
},
"tail": {
"text": "system",
"start": 18,
"end": 24
}
},
{
"head": {
"... | [] |
Two themes have evolved in speech and text image processing work at Xerox PARC that expand and redefine the role of recognition technology in document-oriented applications . | {
"relations": {
"part of": [
{
"head": {
"text": "themes",
"start": 4,
"end": 10
},
"tail": {
"text": "speech and text image processing",
"start": 27,
"end": 59
}
}
],
"used for": [
{
"he... | [] |
One is the development of systems that provide functionality similar to that of text processors but operate directly on audio and scanned image data . | {
"relations": {
"conjunction": [
{
"head": {
"text": "systems",
"start": 26,
"end": 33
},
"tail": {
"text": "text processors",
"start": 80,
"end": 95
}
}
],
"used for": [
{
"head": {
... | [] |
A second , related theme is the use of speech and text-image recognition to retrieve arbitrary , user-specified information from documents with signal content . | {
"relations": {
"used for": [
{
"head": {
"text": "speech and text-image recognition",
"start": 39,
"end": 72
},
"tail": {
"text": "theme",
"start": 19,
"end": 24
}
},
{
"head": {
"text... | [] |
This paper discusses three research initiatives at PARC that exemplify these themes : a text-image editor -LSB- 1 -RSB- , a wordspotter for voice editing and indexing -LSB- 12 -RSB- , and a decoding framework for scanned-document content retrieval -LSB- 4 -RSB- . | {
"relations": {
"hyponym of": [
{
"head": {
"text": "text-image editor",
"start": 88,
"end": 105
},
"tail": {
"text": "research",
"start": 27,
"end": 35
}
},
{
"head": {
"text": "wordsp... | [] |
The problem of predicting image or video interestingness from their low-level feature representations has received increasing interest . | {
"relations": {
"used for": [
{
"head": {
"text": "low-level feature representations",
"start": 68,
"end": 101
},
"tail": {
"text": "predicting image or video interestingness",
"start": 15,
"end": 56
}
}
]... | [] |
To make the annotation less subjective and more reliable , recent studies employ crowdsourcing tools to collect pairwise comparisons -- relying on majority voting to prune the annotation outliers/errors . | {
"relations": {
"used for": [
{
"head": {
"text": "crowdsourcing tools",
"start": 81,
"end": 100
},
"tail": {
"text": "pairwise comparisons",
"start": 112,
"end": 132
}
},
{
"head": {
"... | [] |
In this paper , we propose a more principled way to identify annotation outliers by formulating the interestingness prediction task as a unified robust learning to rank problem , tackling both the outlier detection and interestingness prediction tasks jointly . | {
"relations": {
"used for": [
{
"head": {
"text": "way",
"start": 45,
"end": 48
},
"tail": {
"text": "annotation outliers",
"start": 61,
"end": 80
}
},
{
"head": {
"text": "way",
... | [] |
Extensive experiments on both image and video interestingness benchmark datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "image and video interestingness benchmark datasets",
"start": 30,
"end": 80
},
"tail": {
"text": "approach",
"start": 106,
"end": 114
}
}
],
"comp... | [] |
Many description logics -LRB- DLs -RRB- combine knowledge representation on an abstract , logical level with an interface to `` concrete '' domains such as numbers and strings . | {
"relations": {
"conjunction": [
{
"head": {
"text": "knowledge representation",
"start": 48,
"end": 72
},
"tail": {
"text": "description logics -LRB- DLs -RRB-",
"start": 5,
"end": 39
}
}
]
}
} | [] |
We describe an implementation of data-driven selection of emphatic facial displays for an embodied conversational agent in a dialogue system . | {
"relations": {
"used for": [
{
"head": {
"text": "data-driven selection",
"start": 33,
"end": 54
},
"tail": {
"text": "embodied conversational agent",
"start": 90,
"end": 119
}
},
{
"head": {
... | [] |
The data from those recordings was used in a range of models for generating facial displays , each model making use of a different amount of context or choosing displays differently within a context . | {
"relations": {
"used for": [
{
"head": {
"text": "data",
"start": 4,
"end": 8
},
"tail": {
"text": "models",
"start": 54,
"end": 60
}
},
{
"head": {
"text": "models",
"start"... | [] |
The models were evaluated in two ways : by cross-validation against the corpus , and by asking users to rate the output . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "cross-validation",
"start": 43,
"end": 59
},
"tail": {
"text": "models",
"start": 4,
"end": 10
}
}
]
}
} | [] |
When classifying high-dimensional sequence data , traditional methods -LRB- e.g. , HMMs , CRFs -RRB- may require large amounts of training data to avoid overfitting . | {
"relations": {
"used for": [
{
"head": {
"text": "HMMs",
"start": 83,
"end": 87
},
"tail": {
"text": "classifying high-dimensional sequence data",
"start": 5,
"end": 47
}
},
{
"head": {
... | [] |
In such cases dimensionality reduction can be employed to find a low-dimensional representation on which classification can be done more efficiently . | {
"relations": {
"used for": [
{
"head": {
"text": "dimensionality reduction",
"start": 14,
"end": 38
},
"tail": {
"text": "low-dimensional representation",
"start": 65,
"end": 95
}
},
{
"head": {... | [] |
Existing methods for supervised dimensionality reduction often presume that the data is densely sampled so that a neighborhood graph structure can be formed , or that the data arises from a known distribution . | {
"relations": {
"used for": [
{
"head": {
"text": "Existing methods",
"start": 0,
"end": 16
},
"tail": {
"text": "supervised dimensionality reduction",
"start": 21,
"end": 56
}
}
]
}
} | [] |
Sufficient dimension reduction techniques aim to find a low dimensional representation such that the remaining degrees of freedom become conditionally independent of the output values . | {
"relations": {
"used for": [
{
"head": {
"text": "Sufficient dimension reduction techniques",
"start": 0,
"end": 41
},
"tail": {
"text": "low dimensional representation",
"start": 56,
"end": 86
}
}
]
}
... | [] |
Spatial , temporal and periodic information is combined in a principled manner , and an optimal manifold is learned for the end-task . | {
"relations": {
"used for": [
{
"head": {
"text": "manifold",
"start": 96,
"end": 104
},
"tail": {
"text": "end-task",
"start": 124,
"end": 132
}
}
]
}
} | [] |
We demonstrate the effectiveness of our approach on several tasks involving the discrimination of human gesture and motion categories , as well as on a database of dynamic textures . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "discrimination of human gesture and motion categories",
"start": 80,
"end": 133
},
"tail": {
"text": "approach",
"start": 40,
"end": 48
}
},
{
... | [] |
We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task . | {
"relations": {
"used for": [
{
"head": {
"text": "algorithm",
"start": 24,
"end": 33
},
"tail": {
"text": "chart-based phrase structure parsing",
"start": 38,
"end": 74
}
},
{
"head": {
... | [] |
This is facilitated through the use of phrase boundary heuristics based on the placement of function words , and by heuristic rules that permit certain kinds of phrases to be deduced despite the presence of unknown words . | {
"relations": {
"used for": [
{
"head": {
"text": "function words",
"start": 92,
"end": 106
},
"tail": {
"text": "phrase boundary heuristics",
"start": 39,
"end": 65
}
}
]
}
} | [] |
A further reduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges , thereby reducing the amount of ambiguity and thus the number of edges , since only edges with a valid semantic interpretation are ever introduced . | {
"relations": {
"used for": [
{
"head": {
"text": "semantic",
"start": 61,
"end": 69
},
"tail": {
"text": "reduction in the search space",
"start": 10,
"end": 39
}
}
],
"compare": [
{
"he... | [] |
Automatic estimation of word significance oriented for speech-based Information Retrieval -LRB- IR -RRB- is addressed . | {
"relations": {
"used for": [
{
"head": {
"text": "Automatic estimation of word significance",
"start": 0,
"end": 41
},
"tail": {
"text": "speech-based Information Retrieval -LRB- IR -RRB-",
"start": 55,
"end": 104
... | [] |
Since the significance of words differs in IR , automatic speech recognition -LRB- ASR -RRB- performance has been evaluated based on weighted word error rate -LRB- WWER -RRB- , which gives a weight on errors from the viewpoint of IR , instead of word error rate -LRB- WER -RRB- , which treats all words uniformly . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "weighted word error rate -LRB- WWER -RRB-",
"start": 133,
"end": 174
},
"tail": {
"text": "automatic speech recognition -LRB- ASR -RRB-",
"start": 48,
"end": 92
... | [] |
A decoding strategy that minimizes WWER based on a Minimum Bayes-Risk framework has been shown , and the reduction of errors on both ASR and IR has been reported . | {
"relations": {
"used for": [
{
"head": {
"text": "decoding strategy",
"start": 2,
"end": 19
},
"tail": {
"text": "WWER",
"start": 35,
"end": 39
}
},
{
"head": {
"text": "Minimum Bayes-... | [] |
In this paper , we propose an automatic estimation method for word significance -LRB- weights -RRB- based on its influence on IR . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "automatic estimation method",
"start": 30,
"end": 57
},
"tail": {
"text": "word significance -LRB- weights -RRB-",
"start": 62,
"end": 99
}
}
]
}
} | [] |
Specifically , weights are estimated so that evaluation measures of ASR and IR are equivalent . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "evaluation measures",
"start": 45,
"end": 64
},
"tail": {
"text": "ASR",
"start": 68,
"end": 71
}
},
{
"head": {
"text": "evaluati... | [] |
We apply the proposed method to a speech-based information retrieval system , which is a typical IR system , and show that the method works well . | {
"relations": {
"used for": [
{
"head": {
"text": "method",
"start": 22,
"end": 28
},
"tail": {
"text": "speech-based information retrieval system",
"start": 34,
"end": 75
}
}
],
"hyponym of": [
... | [] |
Methods developed for spelling correction for languages like English -LRB- see the review by Kukich -LRB- Kukich , 1992 -RRB- -RRB- are not readily applicable to agglutinative languages . | {
"relations": {
"used for": [
{
"head": {
"text": "Methods",
"start": 0,
"end": 7
},
"tail": {
"text": "spelling correction",
"start": 22,
"end": 41
}
},
{
"head": {
"text": "spelling c... | [] |
This poster presents an approach to spelling correction in agglutinative languages that is based on two-level morphology and a dynamic-programming based search algorithm . | {
"relations": {
"used for": [
{
"head": {
"text": "approach",
"start": 24,
"end": 32
},
"tail": {
"text": "spelling correction",
"start": 36,
"end": 55
}
},
{
"head": {
"text": "aggluti... | [] |
After an overview of our approach , we present results from experiments with spelling correction in Turkish . | {
"relations": {
"used for": [
{
"head": {
"text": "Turkish",
"start": 100,
"end": 107
},
"tail": {
"text": "spelling correction",
"start": 77,
"end": 96
}
}
]
}
} | [] |
In this paper , we present a novel training method for a localized phrase-based prediction model for statistical machine translation -LRB- SMT -RRB- . | {
"relations": {
"used for": [
{
"head": {
"text": "training method",
"start": 35,
"end": 50
},
"tail": {
"text": "localized phrase-based prediction model",
"start": 57,
"end": 96
}
},
{
"head": {... | [] |
The model predicts blocks with orientation to handle local phrase re-ordering . | {
"relations": {
"used for": [
{
"head": {
"text": "model",
"start": 4,
"end": 9
},
"tail": {
"text": "local phrase re-ordering",
"start": 53,
"end": 77
}
}
]
}
} | [] |
We use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features -LRB- e.g. a language model score -RRB- as well as binary features based on the block identities themselves , e.g. block bigram features . | {
"relations": {
"used for": [
{
"head": {
"text": "maximum likelihood criterion",
"start": 9,
"end": 37
},
"tail": {
"text": "log-linear block bigram model",
"start": 49,
"end": 78
}
},
{
"head":... | [] |
Our training algorithm can easily handle millions of features . | {
"relations": {
"used for": [
{
"head": {
"text": "features",
"start": 53,
"end": 61
},
"tail": {
"text": "training algorithm",
"start": 4,
"end": 22
}
}
]
}
} | [] |
The best system obtains a 18.6 % improvement over the baseline on a standard Arabic-English translation task . | {
"relations": {
"compare": [
{
"head": {
"text": "system",
"start": 9,
"end": 15
},
"tail": {
"text": "baseline",
"start": 54,
"end": 62
}
}
],
"evaluate for": [
{
"head": {
"te... | [] |
In this paper we describe a novel data structure for phrase-based statistical machine translation which allows for the retrieval of arbitrarily long phrases while simultaneously using less memory than is required by current decoder implementations . | {
"relations": {
"used for": [
{
"head": {
"text": "data structure",
"start": 34,
"end": 48
},
"tail": {
"text": "phrase-based statistical machine translation",
"start": 53,
"end": 97
}
},
{
"head... | [] |
We detail the computational complexity and average retrieval times for looking up phrase translations in our suffix array-based data structure . | {
"relations": {
"conjunction": [
{
"head": {
"text": "computational complexity",
"start": 14,
"end": 38
},
"tail": {
"text": "average retrieval times",
"start": 43,
"end": 66
}
}
],
"part of": [
... | [] |
We show how sampling can be used to reduce the retrieval time by orders of magnitude with no loss in translation quality . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "retrieval time",
"start": 47,
"end": 61
},
"tail": {
"text": "sampling",
"start": 12,
"end": 20
}
},
{
"head": {
"text": "translat... | [] |
The major objective of this program is to develop and demonstrate robust , high performance continuous speech recognition -LRB- CSR -RRB- techniques focussed on application in Spoken Language Systems -LRB- SLS -RRB- which will enhance the effectiveness of military and civilian computer-based systems . | {
"relations": {
"used for": [
{
"head": {
"text": "continuous speech recognition -LRB- CSR -RRB- techniques",
"start": 92,
"end": 148
},
"tail": {
"text": "Spoken Language Systems -LRB- SLS -RRB-",
"start": 176,
"end": 215
... | [] |
A key complementary objective is to define and develop applications of robust speech recognition and understanding systems , and to help catalyze the transition of spoken language technology into military and civilian systems , with particular focus on application of robust CSR to mobile military command and control . | {
"relations": {
"used for": [
{
"head": {
"text": "spoken language technology",
"start": 164,
"end": 190
},
"tail": {
"text": "military and civilian systems",
"start": 196,
"end": 225
}
},
{
"hea... | [] |
The research effort focusses on developing advanced acoustic modelling , rapid search , and recognition-time adaptation techniques for robust large-vocabulary CSR , and on applying these techniques to the new ARPA large-vocabulary CSR corpora and to military application tasks . | {
"relations": {
"conjunction": [
{
"head": {
"text": "acoustic modelling",
"start": 52,
"end": 70
},
"tail": {
"text": "rapid search",
"start": 73,
"end": 85
}
},
{
"head": {
"text": "r... | [] |
This paper examines what kind of similarity between words can be represented by what kind of word vectors in the vector space model . | {
"relations": {
"used for": [
{
"head": {
"text": "word vectors",
"start": 93,
"end": 105
},
"tail": {
"text": "similarity between words",
"start": 33,
"end": 57
}
},
{
"head": {
"text"... | [] |
Through two experiments , three methods for constructing word vectors , i.e. , LSA-based , cooccurrence-based and dictionary-based methods , were compared in terms of the ability to represent two kinds of similarity , i.e. , taxonomic similarity and associative similarity . | {
"relations": {
"used for": [
{
"head": {
"text": "methods",
"start": 32,
"end": 39
},
"tail": {
"text": "constructing word vectors",
"start": 44,
"end": 69
}
},
{
"head": {
"text": "LS... | [] |
The result of the comparison was that the dictionary-based word vectors better reflect taxonomic similarity , while the LSA-based and the cooccurrence-based word vectors better reflect associative similarity . | {
"relations": {
"used for": [
{
"head": {
"text": "dictionary-based word vectors",
"start": 42,
"end": 71
},
"tail": {
"text": "taxonomic similarity",
"start": 87,
"end": 107
}
},
{
"head": {
... | [] |
This paper presents a maximum entropy word alignment algorithm for Arabic-English based on supervised training data . | {
"relations": {
"used for": [
{
"head": {
"text": "Arabic-English",
"start": 67,
"end": 81
},
"tail": {
"text": "maximum entropy word alignment algorithm",
"start": 22,
"end": 62
}
},
{
"head": {... | [] |
We demonstrate that it is feasible to create training material for problems in machine translation and that a mixture of supervised and unsupervised methods yields superior performance . | {
"relations": {
"used for": [
{
"head": {
"text": "training material",
"start": 45,
"end": 62
},
"tail": {
"text": "machine translation",
"start": 79,
"end": 98
}
}
]
}
} | [] |
The probabilistic model used in the alignment directly models the link decisions . | {
"relations": {
"used for": [
{
"head": {
"text": "probabilistic model",
"start": 4,
"end": 23
},
"tail": {
"text": "alignment",
"start": 36,
"end": 45
}
},
{
"head": {
"text": "probabi... | [] |
Significant improvement over traditional word alignment techniques is shown as well as improvement on several machine translation tests . | {
"relations": {
"used for": [
{
"head": {
"text": "word alignment techniques",
"start": 41,
"end": 66
},
"tail": {
"text": "machine translation tests",
"start": 110,
"end": 135
}
}
]
}
} | [] |
Performance of the algorithm is contrasted with human annotation performance . | {
"relations": {
"compare": [
{
"head": {
"text": "algorithm",
"start": 19,
"end": 28
},
"tail": {
"text": "human annotation",
"start": 48,
"end": 64
}
}
]
}
} | [] |
In this paper , we propose a novel Cooperative Model for natural language understanding in a dialogue system . | {
"relations": {
"used for": [
{
"head": {
"text": "Cooperative Model",
"start": 35,
"end": 52
},
"tail": {
"text": "natural language understanding",
"start": 57,
"end": 87
}
},
{
"head": {
... | [] |
We build this based on both Finite State Model -LRB- FSM -RRB- and Statistical Learning Model -LRB- SLM -RRB- . | {
"relations": {
"used for": [
{
"head": {
"text": "Finite State Model -LRB- FSM -RRB-",
"start": 28,
"end": 62
},
"tail": {
"text": "this",
"start": 9,
"end": 13
}
},
{
"head": {
"text"... | [] |
FSM provides two strategies for language understanding and have a high accuracy but little robustness and flexibility . | {
"relations": {
"used for": [
{
"head": {
"text": "FSM",
"start": 0,
"end": 3
},
"tail": {
"text": "language understanding",
"start": 32,
"end": 54
}
}
]
}
} | [] |
The ambiguity resolution of right-side dependencies is essential for dependency parsing of sentences with two or more verbs . | {
"relations": {
"used for": [
{
"head": {
"text": "ambiguity resolution of right-side dependencies",
"start": 4,
"end": 51
},
"tail": {
"text": "dependency parsing",
"start": 69,
"end": 87
}
}
]
}
} | [] |
Previous works on shift-reduce dependency parsers may not guarantee the connectivity of a dependency tree due to their weakness at resolving the right-side dependencies . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "connectivity",
"start": 72,
"end": 84
},
"tail": {
"text": "dependency tree",
"start": 90,
"end": 105
}
}
]
}
} | [] |
This paper proposes a two-phase shift-reduce dependency parser based on SVM learning . | {
"relations": {
"used for": [
{
"head": {
"text": "SVM learning",
"start": 72,
"end": 84
},
"tail": {
"text": "two-phase shift-reduce dependency parser",
"start": 22,
"end": 62
}
}
]
}
} | [] |
The left-side dependents and right-side nominal dependents are detected in Phase I , and right-side verbal dependents are decided in Phase II . | {
"relations": {
"conjunction": [
{
"head": {
"text": "left-side dependents",
"start": 4,
"end": 24
},
"tail": {
"text": "right-side nominal dependents",
"start": 29,
"end": 58
}
},
{
"head": {
... | [] |
In experimental evaluation , our proposed method outperforms previous shift-reduce dependency parsers for the Chine language , showing improvement of dependency accuracy by 10.08 % . | {
"relations": {
"compare": [
{
"head": {
"text": "method",
"start": 42,
"end": 48
},
"tail": {
"text": "shift-reduce dependency parsers",
"start": 70,
"end": 101
}
}
],
"evaluate for": [
{
... | [] |
By using commands or rules which are defined to facilitate the construction of format expected or some mathematical expressions , elaborate and pretty documents can be successfully obtained . | {
"relations": {
"conjunction": [
{
"head": {
"text": "commands",
"start": 9,
"end": 17
},
"tail": {
"text": "rules",
"start": 21,
"end": 26
}
}
],
"used for": [
{
"head": {
"tex... | [] |
This paper presents an evaluation method employing a latent variable model for paraphrases with their contexts . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "evaluation method",
"start": 23,
"end": 40
},
"tail": {
"text": "paraphrases",
"start": 79,
"end": 90
}
}
],
"used for": [
{
"head":... | [] |
The results also revealed an upper bound of accuracy of 77 % with the method when using only topic information . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "accuracy",
"start": 44,
"end": 52
},
"tail": {
"text": "method",
"start": 70,
"end": 76
}
}
],
"used for": [
{
"head": {
"... | [] |
We describe the methods and hardware that we are using to produce a real-time demonstration of an integrated Spoken Language System . | {
"relations": {
"conjunction": [
{
"head": {
"text": "methods",
"start": 16,
"end": 23
},
"tail": {
"text": "hardware",
"start": 28,
"end": 36
}
}
],
"used for": [
{
"head": {
"... | [] |
We describe algorithms that greatly reduce the computation needed to compute the N-Best sentence hypotheses . | {
"relations": {
"used for": [
{
"head": {
"text": "algorithms",
"start": 12,
"end": 22
},
"tail": {
"text": "N-Best sentence hypotheses",
"start": 81,
"end": 107
}
}
]
}
} | [] |
To avoid grammar coverage problems we use a fully-connected first-order statistical class grammar . | {
"relations": {
"used for": [
{
"head": {
"text": "fully-connected first-order statistical class grammar",
"start": 44,
"end": 97
},
"tail": {
"text": "grammar coverage problems",
"start": 9,
"end": 34
}
}
... | [] |
The speech-search algorithm is implemented on a board with a single Intel i860 chip , which provides a factor of 5 speed-up over a SUN 4 for straight C code . | {
"relations": {
"used for": [
{
"head": {
"text": "board",
"start": 48,
"end": 53
},
"tail": {
"text": "speech-search algorithm",
"start": 4,
"end": 27
}
},
{
"head": {
"text": "Intel i... | [] |
The board plugs directly into the VME bus of the SUN4 , which controls the system and contains the natural language system and application back end . | {
"relations": {
"used for": [
{
"head": {
"text": "board",
"start": 4,
"end": 9
},
"tail": {
"text": "system",
"start": 75,
"end": 81
}
}
],
"part of": [
{
"head": {
"text": "VM... | [] |
We address the problem of estimating location information of an image using principles from automated representation learning . | {
"relations": {
"used for": [
{
"head": {
"text": "image",
"start": 64,
"end": 69
},
"tail": {
"text": "estimating location information",
"start": 26,
"end": 57
}
},
{
"head": {
"text":... | [] |
We pursue a hierarchical sparse coding approach that learns features useful in discriminating images across locations , by initializing it with a geometric prior corresponding to transformations between image appearance space and their corresponding location grouping space using the notion of parallel transport on mani... | {
"relations": {
"used for": [
{
"head": {
"text": "geometric prior",
"start": 146,
"end": 161
},
"tail": {
"text": "it",
"start": 125,
"end": 127
}
},
{
"head": {
"text": "parallel tran... | [] |
We then extend this approach to account for the availability of heterogeneous data modalities such as geo-tags and videos pertaining to different locations , and also study a relatively under-addressed problem of transferring knowledge available from certain locations to infer the grouping of data from novel locations ... | {
"relations": {
"used for": [
{
"head": {
"text": "approach",
"start": 20,
"end": 28
},
"tail": {
"text": "heterogeneous data modalities",
"start": 64,
"end": 93
}
},
{
"head": {
"text"... | [] |
We evaluate our approach on several standard datasets such as im2gps , San Francisco and MediaEval2010 , and obtain state-of-the-art results . | {
"relations": {
"evaluate for": [
{
"head": {
"text": "datasets",
"start": 45,
"end": 53
},
"tail": {
"text": "approach",
"start": 16,
"end": 24
}
}
],
"hyponym of": [
{
"head": {
... | [] |
Conventional HMMs have weak duration constraints . | {
"relations": {
"feature of": [
{
"head": {
"text": "weak duration constraints",
"start": 23,
"end": 48
},
"tail": {
"text": "HMMs",
"start": 13,
"end": 17
}
}
]
}
} | [] |
In noisy conditions , the mismatch between corrupted speech signals and models trained on clean speech may cause the decoder to produce word matches with unrealistic durations . | {
"relations": {
"used for": [
{
"head": {
"text": "clean speech",
"start": 90,
"end": 102
},
"tail": {
"text": "models",
"start": 72,
"end": 78
}
},
{
"head": {
"text": "decoder",
... | [] |
This paper presents a simple way to incorporate word duration constraints by unrolling HMMs to form a lattice where word duration probabilities can be applied directly to state transitions . | {
"relations": {
"used for": [
{
"head": {
"text": "unrolling HMMs",
"start": 77,
"end": 91
},
"tail": {
"text": "word duration constraints",
"start": 48,
"end": 73
}
},
{
"head": {
"tex... | [] |
The expanded HMMs are compatible with conventional Viterbi decoding . | {
"relations": {
"conjunction": [
{
"head": {
"text": "Viterbi decoding",
"start": 51,
"end": 67
},
"tail": {
"text": "HMMs",
"start": 13,
"end": 17
}
}
]
}
} | [] |
Experiments on connected-digit recognition show that when using explicit duration constraints the decoder generates word matches with more reasonable durations , and word error rates are significantly reduced across a broad range of noise conditions . | {
"relations": {
"used for": [
{
"head": {
"text": "connected-digit recognition",
"start": 15,
"end": 42
},
"tail": {
"text": "decoder",
"start": 98,
"end": 105
}
},
{
"head": {
"text": ... | [] |
One of the claimed benefits of Tree Adjoining Grammars is that they have an extended domain of locality -LRB- EDOL -RRB- . | {
"relations": {
"feature of": [
{
"head": {
"text": "Tree Adjoining Grammars",
"start": 31,
"end": 54
},
"tail": {
"text": "extended domain of locality -LRB- EDOL -RRB-",
"start": 76,
"end": 120
}
}
]
}
... | [] |
We consider how this can be exploited to limit the need for feature structure unification during parsing . | {
"relations": {
"used for": [
{
"head": {
"text": "feature structure unification",
"start": 60,
"end": 89
},
"tail": {
"text": "parsing",
"start": 97,
"end": 104
}
}
]
}
} | [] |
We compare two wide-coverage lexicalized grammars of English , LEXSYS and XTAG , finding that the two grammars exploit EDOL in different ways . | {
"relations": {
"hyponym of": [
{
"head": {
"text": "LEXSYS",
"start": 63,
"end": 69
},
"tail": {
"text": "lexicalized grammars of English",
"start": 29,
"end": 60
}
},
{
"head": {
"tex... | [] |
Identity uncertainty is a pervasive problem in real-world data analysis . | {
"relations": {
"hyponym of": [
{
"head": {
"text": "Identity uncertainty",
"start": 0,
"end": 20
},
"tail": {
"text": "real-world data analysis",
"start": 47,
"end": 71
}
}
]
}
} | [] |
Our approach is based on the use of a relational probability model to define a generative model for the domain , including models of author and title corruption and a probabilistic citation grammar . | {
"relations": {
"used for": [
{
"head": {
"text": "relational probability model",
"start": 38,
"end": 66
},
"tail": {
"text": "approach",
"start": 4,
"end": 12
}
},
{
"head": {
"text": ... | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.