Coral: An Approach for Conversational Agents in Mental Health Applications

It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore b...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Sakhrani, Harsh, Parekh, Saloni, Mahajan, Shubham
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Sakhrani, Harsh
Parekh, Saloni
Mahajan, Shubham
description It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore be empathetic and able to conduct free-flowing conversations. To this effect, we present an approach for creating a generative empathetic open-domain chatbot that can be used for mental health applications. We leverage large scale pre-training and empathetic conversational data to make the responses more empathetic in nature and a multi-turn dialogue arrangement to maintain context. Our models achieve state-of-the-art results on the Empathetic Dialogues test set.
doi_str_mv 10.48550/arxiv.2111.08545
format Article
fullrecord <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2111_08545</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2111_08545</sourcerecordid><originalsourceid>FETCH-LOGICAL-a675-a0420267890efb0721f6456d632985d1cd3f892597017508306927c015f2da6b3</originalsourceid><addsrcrecordid>eNotj01OwzAUhL1hgQoHYIUvkPBsx3_soggoqIhN99FrYlNLxo6cqILb0wZWMxrNjPQRcsegboyU8IDlO5xqzhirwchGXpO3LheMj7RNtJ2mknE4Up8L7XI6uTLjEnLCSNtPl5aZhkTfz-YcbB3G5XjZxDCsrfmGXHmMs7v91w3ZPz_tu221-3h57dpdhUrLCqHhwJU2Fpw_gObMq0aqUQlujRzZMApvLJdWA9MSjABluR6ASc9HVAexIfd_tytMP5XwheWnv0D1K5T4BWF8RS0</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Coral: An Approach for Conversational Agents in Mental Health Applications</title><source>arXiv.org</source><creator>Sakhrani, Harsh ; Parekh, Saloni ; Mahajan, Shubham</creator><creatorcontrib>Sakhrani, Harsh ; Parekh, Saloni ; Mahajan, Shubham</creatorcontrib><description>It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore be empathetic and able to conduct free-flowing conversations. To this effect, we present an approach for creating a generative empathetic open-domain chatbot that can be used for mental health applications. We leverage large scale pre-training and empathetic conversational data to make the responses more empathetic in nature and a multi-turn dialogue arrangement to maintain context. Our models achieve state-of-the-art results on the Empathetic Dialogues test set.</description><identifier>DOI: 10.48550/arxiv.2111.08545</identifier><language>eng</language><subject>Computer Science - Computation and Language</subject><creationdate>2021-11</creationdate><rights>http://creativecommons.org/licenses/by-nc-sa/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2111.08545$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2111.08545$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Sakhrani, Harsh</creatorcontrib><creatorcontrib>Parekh, Saloni</creatorcontrib><creatorcontrib>Mahajan, Shubham</creatorcontrib><title>Coral: An Approach for Conversational Agents in Mental Health Applications</title><description>It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore be empathetic and able to conduct free-flowing conversations. To this effect, we present an approach for creating a generative empathetic open-domain chatbot that can be used for mental health applications. We leverage large scale pre-training and empathetic conversational data to make the responses more empathetic in nature and a multi-turn dialogue arrangement to maintain context. Our models achieve state-of-the-art results on the Empathetic Dialogues test set.</description><subject>Computer Science - Computation and Language</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj01OwzAUhL1hgQoHYIUvkPBsx3_soggoqIhN99FrYlNLxo6cqILb0wZWMxrNjPQRcsegboyU8IDlO5xqzhirwchGXpO3LheMj7RNtJ2mknE4Up8L7XI6uTLjEnLCSNtPl5aZhkTfz-YcbB3G5XjZxDCsrfmGXHmMs7v91w3ZPz_tu221-3h57dpdhUrLCqHhwJU2Fpw_gObMq0aqUQlujRzZMApvLJdWA9MSjABluR6ASc9HVAexIfd_tytMP5XwheWnv0D1K5T4BWF8RS0</recordid><startdate>20211116</startdate><enddate>20211116</enddate><creator>Sakhrani, Harsh</creator><creator>Parekh, Saloni</creator><creator>Mahajan, Shubham</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20211116</creationdate><title>Coral: An Approach for Conversational Agents in Mental Health Applications</title><author>Sakhrani, Harsh ; Parekh, Saloni ; Mahajan, Shubham</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a675-a0420267890efb0721f6456d632985d1cd3f892597017508306927c015f2da6b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Computation and Language</topic><toplevel>online_resources</toplevel><creatorcontrib>Sakhrani, Harsh</creatorcontrib><creatorcontrib>Parekh, Saloni</creatorcontrib><creatorcontrib>Mahajan, Shubham</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sakhrani, Harsh</au><au>Parekh, Saloni</au><au>Mahajan, Shubham</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Coral: An Approach for Conversational Agents in Mental Health Applications</atitle><date>2021-11-16</date><risdate>2021</risdate><abstract>It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore be empathetic and able to conduct free-flowing conversations. To this effect, we present an approach for creating a generative empathetic open-domain chatbot that can be used for mental health applications. We leverage large scale pre-training and empathetic conversational data to make the responses more empathetic in nature and a multi-turn dialogue arrangement to maintain context. Our models achieve state-of-the-art results on the Empathetic Dialogues test set.</abstract><doi>10.48550/arxiv.2111.08545</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.48550/arxiv.2111.08545
ispartof
issn
language eng
recordid cdi_arxiv_primary_2111_08545
source arXiv.org
subjects Computer Science - Computation and Language
title Coral: An Approach for Conversational Agents in Mental Health Applications
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T06%3A08%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Coral:%20An%20Approach%20for%20Conversational%20Agents%20in%20Mental%20Health%20Applications&rft.au=Sakhrani,%20Harsh&rft.date=2021-11-16&rft_id=info:doi/10.48550/arxiv.2111.08545&rft_dat=%3Carxiv_GOX%3E2111_08545%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true