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The anaphoric component is used to define linguistic phenomena such as wh-movement , the passive and the binding of reflexives and pronouns mono-lingually . | {
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The efficiency and quality is exhibited in a live demonstration that recognizes CD-covers from a database of 40000 images of popular music CD 's . | {
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The scheme builds upon popular techniques of indexing descriptors extracted from local regions , and is robust to background clutter and occlusion . | {
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The local region descriptors are hierarchically quantized in a vocabulary tree . | {
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The quantization and the indexing are therefore fully integrated , essentially being one and the same . | {
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The recognition quality is evaluated through retrieval on a database with ground truth , showing the power of the vocabulary tree approach , going as high as 1 million images . | {
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This paper presents a method for blind estimation of reverberation times in reverberant enclosures . | {
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The proposed algorithm is based on a statistical model of short-term log-energy sequences for echo-free speech . | {
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The method has been successfully applied to robust automatic speech recognition in reverberant environments by model selection . | {
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For this application , the reverberation time is first estimated from the reverberated speech utterance to be recognized . | {
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The estimation is then used to select the best acoustic model out of a library of models trained in various artificial re-verberant conditions . | {
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Speech recognition experiments in simulated and real reverberant environments show the efficiency of our approach which outperforms standard channel normaliza-tion techniques . | {
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For one thing , learning methodology applicable in general domains does not readily lend itself in the linguistic domain . | {
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For another , linguistic representation used by language processing systems is not geared to learning . | {
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We introduced a new linguistic representation , the Dynamic Hierarchical Phrasal Lexicon -LRB- DHPL -RRB- -LSB- Zernik88 -RSB- , to facilitate language acquisition . | {
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From this , a language learning model was implemented in the program RINA , which enhances its own lexical hierarchy by processing examples in context . | {
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We identified two tasks : First , how linguistic concepts are acquired from training examples and organized in a hierarchy ; this task was discussed in previous papers -LSB- Zernik87 -RSB- . | {
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Second , we show in this paper how a lexical hierarchy is used in predicting new linguistic concepts . | {
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This paper presents a novel ensemble learning approach to resolving German pronouns . | {
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Experiments show that this approach is superior to a single decision-tree classifier . | {
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Furthermore , we present a standalone system that resolves pronouns in unannotated text by using a fully automatic sequence of preprocessing modules that mimics the manual annotation process . | {
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Although the system performs well within a limited textual domain , further research is needed to make it effective for open-domain question answering and text summarisation . | {
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In this paper , we compare the performance of a state-of-the-art statistical parser -LRB- Bikel , 2004 -RRB- in parsing written and spoken language and in generating sub-categorization cues from written and spoken language . | {
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Although Bikel 's parser achieves a higher accuracy for parsing written language , it achieves a higher accuracy when extracting subcategorization cues from spoken language . | {
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Our experiments also show that current technology for extracting subcategorization frames initially designed for written texts works equally well for spoken language . | {
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Additionally , we explore the utility of punctuation in helping parsing and extraction of subcategorization cues . | {
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Our experiments show that punctuation is of little help in parsing spoken language and extracting subcategorization cues from spoken language . | {
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This paper proposes an alignment adaptation approach to improve domain-specific -LRB- in-domain -RRB- word alignment . | {
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The basic idea of alignment adaptation is to use out-of-domain corpus to improve in-domain word alignment results . | {
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In this paper , we first train two statistical word alignment models with the large-scale out-of-domain corpus and the small-scale in-domain corpus respectively , and then interpolate these two models to improve the domain-specific word alignment . | {
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Experimental results show that our approach improves domain-specific word alignment in terms of both precision and recall , achieving a relative error rate reduction of 6.56 % as compared with the state-of-the-art technologies . | {
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With performance above 97 % accuracy for newspaper text , part of speech -LRB- pos -RRB- tagging might be considered a solved problem . | {
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Previous studies have shown that allowing the parser to resolve pos tag ambiguity does not improve performance . | {
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However , for grammar formalisms which use more fine-grained grammatical categories , for example tag and ccg , tagging accuracy is much lower . | {
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In fact , for these formalisms , premature ambiguity resolution makes parsing infeasible . | {
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We describe a multi-tagging approach which maintains a suitable level of lexical category ambiguity for accurate and efficient ccg parsing . | {
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We extend this multi-tagging approach to the pos level to overcome errors introduced by automatically assigned pos tags . | {
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Although pos tagging accuracy seems high , maintaining some pos tag ambiguity in the language processing pipeline results in more accurate ccg supertagging . | {
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We previously presented a framework for segmentation of complex scenes using multiple physical hypotheses for simple image regions . | {
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A consequence of that framework was a proposal for a new approach to the segmentation of complex scenes into regions corresponding to coherent surfaces rather than merely regions of similar color . | {
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Herein we present an implementation of this new approach and show example segmentations for scenes containing multi-colored piece-wise uniform objects . | {
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Using our approach we are able to intelligently segment scenes with objects of greater complexity than previous physics-based segmentation algorithms . | {
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SmartKom is a multimodal dialog system that combines speech , gesture , and mimics input and output . | {
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Spontaneous speech understanding is combined with the video-based recognition of natural gestures . | {
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... | [] |
One of the major scientific goals of SmartKom is to design new computational methods for the seamless integration and mutual disambiguation of multimodal input and output on a semantic and pragmatic level . | {
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SmartKom is based on the situated delegation-oriented dialog paradigm , in which the user delegates a task to a virtual communication assistant , visualized as a lifelike character on a graphical display . | {
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We describe the SmartKom architecture , the use of an XML-based markup language for multimodal content , and some of the distinguishing features of the first fully operational SmartKom demonstrator . | {
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We present a single-image highlight removal method that incorporates illumination-based constraints into image in-painting . | {
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Constraints provided by observed pixel colors , highlight color analysis and illumination color uniformity are employed in our method to improve estimation of the underlying diffuse color . | {
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The inclusion of these illumination constraints allows for better recovery of shading and textures by inpainting . | {
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In this paper , we propose a novel method , called local non-negative matrix factorization -LRB- LNMF -RRB- , for learning spatially localized , parts-based subspace representation of visual patterns . | {
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An objective function is defined to impose lo-calization constraint , in addition to the non-negativity constraint in the standard NMF -LSB- 1 -RSB- . | {
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An algorithm is presented for the learning of such basis components . | {
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Experimental results are presented to compare LNMF with the NMF and PCA methods for face representation and recognition , which demonstrates advantages of LNMF . | {
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Many AI researchers have investigated useful ways of verifying and validating knowledge bases for ontologies and rules , but it is not easy to directly apply them to checking process models . | {
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Other techniques developed for checking and refining planning knowledge tend to focus on automated plan generation rather than helping users author process information . | {
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In this paper , we propose a complementary approach which helps users author and check process models . | {
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It builds interdepen-dency models from this analysis and uses them to find errors and propose fixes . | {
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In this paper , we describe the research using machine learning techniques to build a comma checker to be integrated in a grammar checker for Basque . | {
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After several experiments , and trained with a little corpus of 100,000 words , the system guesses correctly not placing commas with a precision of 96 % and a recall of 98 % . | {
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It also gets a precision of 70 % and a recall of 49 % in the task of placing commas . | {
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The present paper reports on a preparatory research for building a language corpus annotation scenario capturing the discourse relations in Czech . | {
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We primarily focus on the description of the syntactically motivated relations in discourse , basing our findings on the theoretical background of the Prague Dependency Treebank 2.0 and the Penn Discourse Treebank 2 . | {
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"text": "syntactically motivated relations in discourse",
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... | [] |
Our aim is to revisit the present-day syntactico-semantic -LRB- tectogrammatical -RRB- annotation in the Prague Dependency Treebank , extend it for the purposes of a sentence-boundary-crossing representation and eventually to design a new , discourse level of annotation . | {
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... | [] |
In this paper , we propose a feasible process of such a transfer , comparing the possibilities the Praguian dependency-based approach offers with the Penn discourse annotation based primarily on the analysis and classification of discourse connectives . | {
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Regression-based techniques have shown promising results for people counting in crowded scenes . | {
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However , most existing techniques require expensive and laborious data annotation for model training . | {
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},
{
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-LRB- 2 -RRB- Rather than learning from only labelled data , the abundant unlabelled data are exploited . | {
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} | [] |
All three ideas are implemented in a unified active and semi-supervised regression framework with ability to perform transfer learning , by exploiting the underlying geometric structure of crowd patterns via manifold analysis . | {
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... | [] |
Representing images with layers has many important applications , such as video compression , motion analysis , and 3D scene analysis . | {
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This paper presents an approach to reliably extracting layers from images by taking advantages of the fact that homographies induced by planar patches in the scene form a low dimensional linear subspace . | {
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Layers in the input images will be mapped in the subspace , where it is proven that they form well-defined clusters and can be reliably identified by a simple mean-shift based clustering algorithm . | {
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Global optimality is achieved since all valid regions are simultaneously taken into account , and noise can be effectively reduced by enforcing the subspace constraint . | {
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} | [] |
The construction of causal graphs from non-experimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the graph . | {
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These constraints are of two types : conditional inde-pendencies and algebraic constraints , first noted by Verma . | {
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},
{
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While conditional independencies are well studied and frequently used in causal induction algorithms , Verma constraints are still poorly understood , and rarely applied . | {
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... | [] |
In this paper we examine a special subset of Verma constraints which are easy to understand , easy to identify and easy to apply ; they arise from '' dormant independencies , '' namely , conditional independencies that hold in interventional distributions . | {
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"conjunction": [
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We give a complete algorithm for determining if a dormant independence between two sets of variables is entailed by the causal graph , such that this independence is identifiable , in other words if it resides in an interventional distribution that can be predicted without resorting to interventions . | {
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We further show the usefulness of dormant independencies in model testing and induction by giving an algorithm that uses constraints entailed by dormant independencies to prune extraneous edges from a given causal graph . | {
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{
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With the recent popularity of animated GIFs on social media , there is need for ways to index them with rich meta-data . | {
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"head": {
"text": "social media",
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"text": "animated GIFs",
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]
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} | [] |
To advance research on animated GIF understanding , we collected a new dataset , Tumblr GIF -LRB- TGIF -RRB- , with 100K animated GIFs from Tumblr and 120K natural language descriptions obtained via crowdsourcing . | {
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},
{
"head": {
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The motivation for this work is to develop a testbed for image sequence description systems , where the task is to generate natural language descriptions for animated GIFs or video clips . | {
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"used for": [
{
"head": {
"text": "natural language descriptions",
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"tail": {
"text": "animated GIFs",
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},
{
"head": {
... | [] |
To ensure a high quality dataset , we developed a series of novel quality controls to validate free-form text input from crowd-workers . | {
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} | [] |
We show that there is unambiguous association between visual content and natural language descriptions in our dataset , making it an ideal benchmark for the visual content captioning task . | {
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"conjunction": [
{
"head": {
"text": "visual content",
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"tail": {
"text": "natural language descriptions",
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],
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... | [] |
We perform extensive statistical analyses to compare our dataset to existing image and video description datasets . | {
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"head": {
"text": "dataset",
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"end": 64
},
"tail": {
"text": "image and video description datasets",
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}
}
]
}
} | [] |
Next , we provide baseline results on the animated GIF description task , using three representative techniques : nearest neighbor , statistical machine translation , and recurrent neural networks . | {
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"used for": [
{
"head": {
"text": "representative techniques",
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],
"hyponym of": ... | [] |
Finally , we show that models fine-tuned from our animated GIF description dataset can be helpful for automatic movie description . | {
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{
"head": {
"text": "animated GIF description dataset",
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"tail": {
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} | [] |
Systemic grammar has been used for AI text generation work in the past , but the implementations have tended be ad hoc or inefficient . | {
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{
"head": {
"text": "Systemic grammar",
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"text": "AI text generation",
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]
}
} | [] |
This paper presents an approach to systemic text generation where AI problem solving techniques are applied directly to an unadulterated systemic grammar . | {
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"head": {
"text": "approach",
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"tail": {
"text": "text generation",
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},
{
"head": {
"text": "AI problem ... | [] |
This approach is made possible by a special relationship between systemic grammar and problem solving : both are organized primarily as choosing from alternatives . | {
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"conjunction": [
{
"head": {
"text": "systemic grammar",
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"tail": {
"text": "problem solving",
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]
}
} | [] |
The result is simple , efficient text generation firmly based in a linguistic theory . | {
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"text": "linguistic theory",
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"tail": {
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} | [] |
In this paper a novel solution to automatic and unsupervised word sense induction -LRB- WSI -RRB- is introduced . | {
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{
"head": {
"text": "solution",
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"tail": {
"text": "automatic and unsupervised word sense induction -LRB- WSI -RRB-",
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}... | [] |
It represents an instantiation of the one sense per collocation observation -LRB- Gale et al. , 1992 -RRB- . | {
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"hyponym of": [
{
"head": {
"text": "It",
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"text": "one sense per collocation observation",
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}
]
}
} | [] |
Like most existing approaches it utilizes clustering of word co-occurrences . | {
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} | [] |
This approach differs from other approaches to WSI in that it enhances the effect of the one sense per collocation observation by using triplets of words instead of pairs . | {
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"compare": [
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"head": {
"text": "approach",
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],
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The combination with a two-step clustering process using sentence co-occurrences as features allows for accurate results . | {
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"head": {
"text": "sentence co-occurrences",
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"tail": {
"text": "two-step clustering process",
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"end": 50
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]
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} | [] |
Additionally , a novel and likewise automatic and unsupervised evaluation method inspired by Schutze 's -LRB- 1992 -RRB- idea of evaluation of word sense disambiguation algorithms is employed . | {
"relations": {
"evaluate for": [
{
"head": {
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"tail": {
"text": "word sense disambiguation algorithms",
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... | [] |
Offering advantages like reproducability and independency of a given biased gold standard it also enables automatic parameter optimization of the WSI algorithm . | {
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"head": {
"text": "automatic parameter optimization",
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"tail": {
"text": "WSI algorithm",
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}
} | [] |
This abstract describes a natural language system which deals usefully with ungrammatical input and describes some actual and potential applications of it in computer aided second language learning . | {
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"head": {
"text": "natural language system",
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"tail": {
"text": "ungrammatical input",
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}
},
{
"head": {
"... | [] |
However , this is not the only area in which the principles of the system might be used , and the aim in building it was simply to demonstrate the workability of the general mechanism , and provide a framework for assessing developments of it . | {
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}
} | [] |
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