Генерация референтных выражений

task ID: referringexpressiongeneration

Related Papers

Cooking Up Referring Expressions

Authors: nan

Publication: TIPSTER (1989)

DOI: nan

This paper describes the referring expression generation mechanisms used in EPICURE, a com- puter program which produces natural language descriptions of cookery recipes. Major features of the system include: an …...

35873

Sentence generation as a planning problem

Authors: nan

Publication: TIPSTER (2007)

DOI: nan

We translate sentence generation from TAG grammars with semantic and pragmatic in- formation into a planning problem by encod- ing the contribution of each word declara- tively and explicitly. This …...

36507

Trainable Speaker-Based Referring Expression Generation

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

Previous work in referring expression gen- eration has explored general purpose tech- niques for attribute selection and surface realization. However, most of this work did not take into account: a) …...

42264

Learning to Adapt to Unknown Users: Referring Expression Generation in Spoken Dialogue Systems

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

We present a data-driven approach to learn user-adaptive referring expression gener- ation (REG) policies for spoken dialogue systems. Referring expressions can be dif- ficult to understand in technical domains where …...

36230

Speaker-Dependent Variation in Content Selection for Referring Expression Generation

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

In this paper we describe machine learn- ing experiments that aim to characterise the content selection process for distin- guishing descriptions. Our experiments are based on two large corpora of …...

28637

Generating Subsequent Reference in Shared Visual Scenes: Computation vs Re-Use

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

Traditional computational approaches to re- ferring expression generation operate in a de- liberate manner, choosing the attributes to be included on the basis of their ability to dis- tinguish the …...

44219

On The Feasibility of Open Domain Referring Expression Generation Using Large Scale Folksonomies

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

Generating referring expressions has received considerable attention in Natural Language Generation. In recent years we start seeing deployments of referring expression genera- tors moving away from limited domains with custom-made …...

23832

Justifying Corpus-Based Choices in Referring Expression Generation

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Most empirically-based approaches to NL generation elaborate on co-occur- rences and frequencies observed over a corpus, which are then accommodated by learning algorithms. This method fails to capture generalities in …...

28999

Learning Distributions over Logical Forms for Referring Expression Generation

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

We present a new approach to referring ex- pression generation, casting it as a density es- timation problem where the goal is to learn distributions over logical expressions identi- fying …...

34496

From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

Predicting the success of referring expres- sions (RE) is vital for real-world applica- tions such as navigation systems. Tradi- tionally, research has focused on studying Referring Expression Generation (REG) in …...

34392

The Methodius Corpus of Rhetorical Discourse Structures and Generated Texts

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractUsing the Methodius Natural Language Generation (NLG) System, we have created a corpus which consists of a collection of generated texts which describe ancient Greek artefacts. Each text is linked …...

16210

Definite Description Lexical Choice: taking Speaker’s Personality into account

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

In Natural Language Generation (NLG), Referring Expression Generation (REG) lexical choice is the subtask that provides words to express a given input meaning representation. Since lexical choices made in real …...

17547

Reference production in human-computer interaction: Issues for Corpus-based Referring Expression Generation

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

In the Natural Language Generation field, Referring Expression Generation (REG) studies often make use of experiments involving human subjects for the collection of corpora of definite descriptions. Experiments of this …...

17548

Referring Expression Generation in time-constrained communication

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

In game-like applications and many others, an underlying Natural Language Generation system may have to express urgency or other dynamic aspects of a fast-evolving situation as text, which may be …...

17545

Referring Expression Generation Using Entity Profiles

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractReferring Expression Generation (REG) is the task of generating contextually appropriate references to entities. A limitation of existing REG systems is that they rely on entity-specific supervised training, which means …...

7610

Referring to what you know and do not know: Making Referring Expression Generation Models Generalize To Unseen Entities

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractData-to-text Natural Language Generation (NLG) is the computational process of generating natural language in the form of text or voice from non-linguistic data. A core micro-planning task within NLG is …...

4150

Keeping an Eye on Context: Attention Allocation over Input Partitions in Referring Expression Generation

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractIn Referring Expression Generation, model inputs are often composed of different representations, including the visual properties of the intended referent, its relative position and size, and the visual context. Yet, …...

27291