Publikace UTB
Repozitář publikační činnosti UTB

Implementing call bots: An architectural guide

Repozitář DSpace/Manakin

Zobrazit minimální záznam


dc.title Implementing call bots: An architectural guide en
dc.contributor.author Kováč, Jozef
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Viktorin, Adam
dc.relation.ispartof Artificial Intelligence and Soft Computing, ICAISC 2024, Pt II
dc.identifier.issn 2945-9133 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 1611-3349 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9789819698936
dc.identifier.isbn 9789819698042
dc.identifier.isbn 9789819698110
dc.identifier.isbn 9789819698905
dc.identifier.isbn 9789819512324
dc.identifier.isbn 9783032026019
dc.identifier.isbn 9783032008909
dc.identifier.isbn 9783031915802
dc.identifier.isbn 9789819698141
dc.identifier.isbn 9783031984136
dc.date.issued 2025
utb.relation.volume 15165
dc.citation.spage 298
dc.citation.epage 310
dc.event.title 23rd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2024
dc.event.location Zakopane
utb.event.state-en Polsko
utb.event.state-cs Zakopané
dc.event.sdate 2024-06-16
dc.event.edate 2024-06-20
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-031-84356-3_24
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-031-84356-3_24
dc.subject call bot en
dc.subject software architecture en
dc.subject Large Language Models en
dc.subject conversational agent en
dc.subject Architecture en
dc.subject Artificial Intelligence en
dc.subject Bot (internet) en
dc.subject Information Systems en
dc.subject Software Agents en
dc.subject Software Prototyping en
dc.subject Business Case en
dc.subject Business-oriented en
dc.subject Call Bot en
dc.subject Conversational Agents en
dc.subject Language Model en
dc.subject Large Language Model en
dc.subject Performance en
dc.subject Phone Calls en
dc.subject Real-time Voice en
dc.subject Software Architecture en
dc.description.abstract This paper proposes an architectural and technological recommendation for constructing a call bot to access the possibility of interaction with generative AI in the form of large language models via standard GSM-transferred phone calls. In an effort to establish a loose template to guide business-oriented call bot implementations, a real-time voice-processing pipeline was established and thoroughly described using a selection of commercially available AI-based technologies and their interconnection, resulting in the creation of a prototype application. The paper further explains the roles of used technologies and their usage, illustrates the used architecture, and evaluates our solution’s actual business-case success performance compared to openly available generic call automatons. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1012536
utb.identifier.scopus 2-s2.0-105010248949
utb.identifier.wok 001535049000024
utb.source C-wok
dc.date.accessioned 2025-10-16T07:25:47Z
dc.date.available 2025-10-16T07:25:47Z
dc.description.sponsorship The research presented in this paper was supported by: the Internal Grant Agency of the Tomas Bata University in Zlin-IGA/CebiaTech/2023/004, and resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz). The described call bot implementation was achieved in cooperation with the company Blogic s.r.o., using production use-case data provided by one of its partners. All data used for evaluation have been thoroughly anonymized, and authors were permitted to publish this information by the company\u2019s management.
dc.description.sponsorship Internal Grant Agency of the Tomas Bata University in Zlin [IGA/CebiaTech/2023/004]; Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz)
utb.ou Department of Informatics and Artificial Intelligence
utb.contributor.internalauthor Kováč, Jozef
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Viktorin, Adam
utb.fulltext.sponsorship The research presented in this paper was supported by: the Internal Grant Agency of the Tomas Bata University in Zlin - IGA/CebiaTech/2023/004, and resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.wos.affiliation [Kovac, Jozef; Senkerik, Roman; Viktorin, Adam] Tomas Bata Univ Zlin, Dept Informat & Artificial Intelligence, Fac Appl Informat, Nad Stranemi 4511, Zlin 76005, Czech Republic
utb.scopus.affiliation Tomas Bata University in Zlin, Zlin, Czech Republic
utb.fulltext.projects IGA/CebiaTech/2023/004
Find Full text

Soubory tohoto záznamu

Soubory Velikost Formát Zobrazit

K tomuto záznamu nejsou připojeny žádné soubory.

Zobrazit minimální záznam