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Found 33 papers, 5 papers with code
Pseudo Ambiguous and Clarifying Questions Based on Sentence Structures Toward Clarifying Question Answering System
Ambiguous questions are generated by eliminating a part of a sentence considering the sentence structure.
Overview of the IWSLT 2017 Evaluation Campaign
The IWSLT 2017 evaluation campaign has organised three tasks.
Whats New? Identifying the Unfolding of New Events in Narratives
We publish the annotated dataset, annotation materials, and machine learning baseline models for the task of new event extraction for narrative understanding.
ARTA: Collection and Classification of Ambiguous Requests and Thoughtful Actions
In order to train the classification model on such training data, we applied the positive/unlabeled (PU) learning method, which assumes that only a part of the data is labeled with positive examples.
Improving Spoken Language Understanding by Wisdom of Crowds
Spoken language understanding (SLU), which converts user requests in natural language to machine-interpretable expressions, is becoming an essential task.
Reflection-based Word Attribute Transfer
For transferring king into queen in this analogy-based manner, we subtract a difference vector man - woman based on the knowledge that king is male.
Emotional Speech Corpus for Persuasive Dialogue System
Expressing emotion is known as an efficient way to persuade one{'}s dialogue partner to accept one{'}s claim or proposal.
Caption Generation of Robot Behaviors based on Unsupervised Learning of Action Segments
Two reasons make it challenging to apply existing sequence-to-sequence models to this mapping: 1) it is hard to prepare a large-scale dataset for any kind of robots and their environment, and 2) there is a gap between the number of samples obtained from robot action observations and generated word sequences of captions.
Neural Conversation Model Controllable by Given Dialogue Act Based on Adversarial Learning and Label-aware Objective
We introduce an adversarial learning framework for the task of generating conditional responses with a new objective to a discriminator, which explicitly distinguishes sentences by using labels.
Conversational Response Re-ranking Based on Event Causality and Role Factored Tensor Event Embedding
We propose a novel method for selecting coherent and diverse responses for a given dialogue context.
An Incremental Turn-Taking Model For Task-Oriented Dialog Systems
To identify the point of maximal understanding in an ongoing utterance, we a) implement an incremental Dialog State Tracker which is updated on a token basis (iDST) b) re-label the Dialog State Tracking Challenge 2 (DSTC2) dataset and c) adapt it to the incremental turn-taking experimental scenario.
Dialog System Technology Challenge 7
This paper introduces the Seventh Dialog System Technology Challenges (DSTC), which use shared datasets to explore the problem of building dialog systems.
Optimization of Information-Seeking Dialogue Strategy for Argumentation-Based Dialogue System
It is required that these systems have sufficient supporting information to argue their claims rationally; however, the systems often do not have enough of such information in realistic situations.
Another Diversity-Promoting Objective Function for Neural Dialogue Generation
Although generation-based dialogue systems have been widely researched, the response generations by most existing systems have very low diversities.
Unsupervised Counselor Dialogue Clustering for Positive Emotion Elicitation in Neural Dialogue System
Positive emotion elicitation seeks to improve user{'}s emotional state through dialogue system interaction, where a chat-based scenario is layered with an implicit goal to address user{'}s emotional needs.
Interactive Image Manipulation with Natural Language Instruction Commands
We propose an interactive image-manipulation system with natural language instruction, which can generate a target image from a source image and an instruction that describes the difference between the source and the target image.
Acquisition and Assessment of Semantic Content for the Generation of Elaborateness and Indirectness in Spoken Dialogue Systems
Defining all possible system actions in a dialogue system by hand is a tedious work.
Information Navigation System with Discovering User Interests
We demonstrate an information navigation system for sightseeing domains that has a dialogue interface for discovering user interests for tourist activities.
An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation
Training of neural machine translation (NMT) models usually uses mini-batches for efficiency purposes.
Analysis of the Effect of Dependency Information on Predicate-Argument Structure Analysis and Zero Anaphora Resolution
This paper investigates and analyzes the effect of dependency information on predicate-argument structure analysis (PASA) and zero anaphora resolution (ZAR) for Japanese, and shows that a straightforward approach of PASA and ZAR works effectively even if dependency information was not available.
Neural Machine Translation via Binary Code Prediction
In this paper, we propose a new method for calculating the output layer in neural machine translation systems.
Construction of Japanese Audio-Visual Emotion Database and Its Application in Emotion Recognition
Emotional aspects play a vital role in making human communication a rich and dynamic experience.
