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Dialogue systems should provide a cooperative informational dialogue aimed at knowledge sharing . In the paper speech acts of assertion (SAA) are assumed to be the means of achieving this …...

We describe a general framework for encoding rich domain mod- els and sophisticated plan reasoning capabilities. The approach uses graph-basedreasoning to address a wide range of tasks that typically arise …...

In this paper we report on our work on a prototype route navigation dialogue system for use in a vehicle. The system delivers spoken turn-by-turn directions, and has been developed …...

Developing dialogue systems is a complex pro- cess. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develop them and no sure …...

Spoken language generation for dialogue systems requires a dictionary of mappings between semantic representations of con- cepts the system wants to express and re- alizations of those concepts. Dictionary creation …...

Automatically extracting social meaning and intention from spoken dialogue is an impor- tant task for dialogue systems and social com- puting. We describe a system for detecting elements of interactional …...

Sarcasm is a form of speech act in which the speakers convey their message in an implicit way. The inherently ambiguous nature of sarcasm sometimes makes it hard even for …...

Robustness and portability of spoken language understanding systems among languages and domains : the PORTMEDIA project The ANR PORTMEDIA projet aimed at complementing the MEDIA corpus so as to foster …...

. Incremental dialogue is at the heart of current research in the field of dialogue systems. Several archi- tectures and models have been published such as (Allen et al., 2001; …...

This paper presents predicate-argument structure analysis (PASA) for dialogue systems in Japanese. Conventional PASA and semantic role labeling have been applied to newspaper arti- cles. Because pronominalization and ellipses frequently …...

Dialogue systems that support users in complex problem solving must interpret user utterances within the context of a dy- namically changing, user-created problem solving artifact. This paper presents a novel …...

AbstractCollecting spontaneous speech corpora that are open-ended, yet topically constrained, is increasingly popular for research in spoken dialogue systems and speaker state, inter alia. Typically, these corpora are labeled by …...

This article gives a general overview of five AI language-related projects that address contemporary Romanian language, in both textual and speech form, language related applications, as well as collections of …...

Dialogue systems for hotel and tourist information have typically simplified the richness of the domain, focusing system utterances on only a few selected attributes such as price, location and type …...

AbstractIntent classification is an important building block of dialogue systems. With the burgeoning of conversational AI, existing systems are not capable of handling numerous fast-emerging intents, which motivates zero-shot intent …...

AbstractHow to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans. To handle this problem, memory networks are usually a …...

AbstractRetrieving the proper knowledge relevant to conversational context is an important challenge in dialogue systems, to engage users with more informative response. Several recent works propose to formulate this knowledge …...

AbstractEmotion recognition in dialogue systems has gained attention in the field of natural language processing recent years, because it can be applied in opinion mining from public conversational data on …...

AbstractIn many domains, dialogue systems need to work collaboratively with users to successfully reconstruct the meaning the user had in mind. In this paper, we show how cognitive models of …...

AbstractRecently there are increasing concerns about the fairness of Artificial Intelligence (AI) in real-world applications such as computer vision and recommendations. For example, recognition algorithms in computer vision are unfair …...

AbstractUser attributes provide rich and useful information for user understanding, yet structured and easy-to-use attributes are often sparsely populated. In this paper, we leverage dialogues with conversational agents, which contain …...

AbstractThe ubiquitous nature of dialogue systems and their interaction with users generate an enormous amount of data. Can we improve chatbots using this data? A self-feeding chatbot improves itself by …...

AbstractDialogue systems play an increasingly important role in various aspects of our daily life. It is evident from recent research that dialogue systems trained on human conversation data are biased. …...

AbstractIn the recent past, dialogue systems have gained immense popularity and have become ubiquitous. During conversations, humans not only rely on languages but seek contextual information through visual contents as …...

AbstractWe present a new dataset of TED-talks annotated with the questions they evoke and, where available, the answers to these questions. Evoked questions represent a hitherto mostly unexplored type of …...

AbstractDialogue systems for interaction with humans have been enjoying increased popularity in the research and industry fields. To this day, the best way to estimate their success is through means …...

AbstractDeep neural networks have become the standard approach to building reliable Natural Language Processing (NLP) applications, ranging from Neural Machine Translation (NMT) to dialogue systems. However, improving accuracy by increasing …...

An important aspect of developing dialogue systems is how to evaluate and compare the performance of different systems. Existing au- tomatic evaluation metrics are based on turn- level quality evaluation …...

AbstractAlthough neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities. To this end, we exploit Abstract …...

AbstractTo improve the coherence and knowledge retrieval capabilities of non-task-oriented dialogue systems, recent Transformer-based models aim to integrate fixed background context. This often comes in the form of knowledge graphs, …...

AbstractAutomatic dialogue coherence evaluation has attracted increasing attention and is crucial for developing promising dialogue systems. However, existing metrics have two major limitations: (a) they are mostly trained in a …...

AbstractSeveral dialogue corpora are currently available for research purposes, but they still fall short for the growing interest in the development of dialogue systems with their own specific requirements. In …...

AbstractName Entity Recognition (NER) is a very important and basic task in traditional NLP tasks. In the biomedical field, NER tasks have been widely used in various products developed by …...

AbstractDiscourse parsing on multi-party dialogues is an important but difficult task in dialogue systems and conversational analysis. It is believed that speaker interactions are helpful for this task. However, most …...

AbstractAs an important task to analyze the semantic structure of a sentence, semantic role labeling (SRL) aims to locate the semantic role (e.g., agent) of noun phrases with respect to …...