Conversational Search -- A Report from Dagstuhl Seminar 19461
- URL: http://arxiv.org/abs/2005.08658v1
- Date: Mon, 18 May 2020 12:48:33 GMT
- Title: Conversational Search -- A Report from Dagstuhl Seminar 19461
- Authors: Avishek Anand, Lawrence Cavedon, Matthias Hagen, Hideo Joho, Mark
Sanderson, and Benno Stein
- Abstract summary: 44researchers in Information Retrieval and Web Search, Natural Language Processing, Human Computer Interaction, and Dialogue Systems were invited.
A 5-day program of the seminar consisted of six introductory and background sessions, three visionary talk sessions, one industry talk session, and seven working groups and reporting sessions.
This report provides the executive summary, overview of invited talks, and findings from the seven working groups which cover the definition, evaluation, modelling, explanation, scenarios, applications, and prototype of Conversational Search.
- Score: 32.97401872105722
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Dagstuhl Seminar 19461 "Conversational Search" was held on 10-15 November
2019. 44~researchers in Information Retrieval and Web Search, Natural Language
Processing, Human Computer Interaction, and Dialogue Systems were invited to
share the latest development in the area of Conversational Search and discuss
its research agenda and future directions. A 5-day program of the seminar
consisted of six introductory and background sessions, three visionary talk
sessions, one industry talk session, and seven working groups and reporting
sessions. The seminar also had three social events during the program. This
report provides the executive summary, overview of invited talks, and findings
from the seven working groups which cover the definition, evaluation,
modelling, explanation, scenarios, applications, and prototype of
Conversational Search. The ideas and findings presented in this report should
serve as one of the main sources for diverse research programs on
Conversational Search.
Related papers
- WavChat: A Survey of Spoken Dialogue Models [66.82775211793547]
Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o, have captured significant attention in the speech domain.
These advanced spoken dialogue models not only comprehend audio, music, and other speech-related features, but also capture stylistic and timbral characteristics in speech.
Despite the progress in spoken dialogue systems, there is a lack of comprehensive surveys that systematically organize and analyze these systems.
arXiv Detail & Related papers (2024-11-15T04:16:45Z) - A Conceptual Framework for Conversational Search and Recommendation: Conceptualizing Agent-Human Interactions During the Conversational Search Process [3.2114882156161824]
The conversational search task aims to enable a user to resolve information needs via natural language dialogue with an agent.
We aim to develop a conceptual framework of the actions and intents of users and agents explaining how these actions enable the user to explore the search space and resolve their information need.
arXiv Detail & Related papers (2024-04-12T17:48:18Z) - Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium [71.81297744767885]
Third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA.
We organized eleven in-person roundtables and four virtual roundtables at ML4H 2022.
This document serves as a comprehensive review paper, summarizing the recent advancements in machine learning for healthcare.
arXiv Detail & Related papers (2024-03-03T22:21:58Z) - Findings of the First Workshop on Simulating Conversational Intelligence in Chat [29.09249285901475]
The aim of the workshop was to bring together experts working on open-domain dialogue research.
The main goal of this paper is to provide an overview of the shared task, and an in depth analysis of the shared task results following presentation at the workshop.
arXiv Detail & Related papers (2024-02-09T14:08:23Z) - NewsDialogues: Towards Proactive News Grounded Conversation [72.10055780635625]
We propose a novel task, Proactive News Grounded Conversation, in which a dialogue system can proactively lead the conversation based on some key topics of the news.
To further develop this novel task, we collect a human-to-human Chinese dialogue dataset tsNewsDialogues, which includes 1K conversations with a total of 14.6K utterances.
arXiv Detail & Related papers (2023-08-12T08:33:42Z) - SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented
Dialogue Agents [72.42049370297849]
SpokenWOZ is a large-scale speech-text dataset for spoken TOD.
Cross-turn slot and reasoning slot detection are new challenges for SpokenWOZ.
arXiv Detail & Related papers (2023-05-22T13:47:51Z) - Advancing an Interdisciplinary Science of Conversation: Insights from a
Large Multimodal Corpus of Human Speech [0.12038936091716987]
In this report we advance an interdisciplinary science of conversation, with findings from a large, multimodal corpus of 1,656 recorded conversations in spoken English.
This 7+ million word, 850 hour corpus totals over 1TB of audio, video, and transcripts, with moment-to-moment measures of vocal, facial, and semantic expression.
We report (5) a comprehensive mixed-method report, based on quantitative analysis and qualitative review of each recording, that showcases how individuals from diverse backgrounds alter their communication patterns and find ways to connect.
arXiv Detail & Related papers (2022-03-01T18:50:33Z) - DialogLM: Pre-trained Model for Long Dialogue Understanding and
Summarization [19.918194137007653]
We present a pre-training framework for long dialogue understanding and summarization.
Considering the nature of long conversations, we propose a window-based denoising approach for generative pre-training.
We conduct extensive experiments on five datasets of long dialogues, covering tasks of dialogue summarization, abstractive question answering and topic segmentation.
arXiv Detail & Related papers (2021-09-06T13:55:03Z) - Challenges and Applications of Automated Extraction of Socio-political
Events from Text (CASE 2021): Workshop and Shared Task Report [4.464102544889847]
This workshop is the fourth issue of a series of workshops on automatic extraction of socio-political events from news.
The purpose of this series of workshops is to foster research and development of reliable, valid, robust, and practical solutions.
arXiv Detail & Related papers (2021-08-17T20:29:49Z) - Dialogue-Based Relation Extraction [53.2896545819799]
We present the first human-annotated dialogue-based relation extraction (RE) dataset DialogRE.
We argue that speaker-related information plays a critical role in the proposed task, based on an analysis of similarities and differences between dialogue-based and traditional RE tasks.
Experimental results demonstrate that a speaker-aware extension on the best-performing model leads to gains in both the standard and conversational evaluation settings.
arXiv Detail & Related papers (2020-04-17T03:51:57Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.