Voice-Controlled Intelligent Personal Assistant for Call-Center Automation in the Uzbek Language
DC Field | Value | Language |
---|---|---|
dc.contributor.author | NURALIEVICH, MUKHAMADIYEV ABDINABI | - |
dc.contributor.author | Khujayarov, Ilyos | - |
dc.contributor.author | Cho, Jinsoo | - |
dc.date.accessioned | 2023-12-20T03:30:17Z | - |
dc.date.available | 2023-12-20T03:30:17Z | - |
dc.date.issued | 2023-12 | - |
dc.identifier.issn | 2079-9292 | - |
dc.identifier.issn | 2079-9292 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89696 | - |
dc.description.abstract | The demand for customer support call centers has surged across various sectors due to the pandemic. Yet, the constraints of round-the-clock human services and fluctuating wait times pose challenges in fully meeting customer needs. In response, there's a growing need for automated customer service systems that can provide responses tailored to specific domains and in the native languages of customers, particularly in developing nations like Uzbekistan where call center usage is on the rise. Our system, "UzAssistant," is designed to recognize user voices and accurately present customer issues in standardized Uzbek, as well as vocalize the responses to voice queries. It employs feature extraction and recurrent neural network (RNN)-based models for effective automatic speech recognition, achieving an impressive 96.4% accuracy in real-time tests with 56 participants. Additionally, the system incorporates a sentence similarity assessment method and a text-to-speech (TTS) synthesis feature specifically for the Uzbek language. The TTS component utilizes the WaveNet architecture to convert text into speech in Uzbek. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI | - |
dc.title | Voice-Controlled Intelligent Personal Assistant for Call-Center Automation in the Uzbek Language | - |
dc.type | Article | - |
dc.identifier.wosid | 001116652800001 | - |
dc.identifier.doi | 10.3390/electronics12234850 | - |
dc.identifier.bibliographicCitation | ELECTRONICS, v.12, no.23 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85179330529 | - |
dc.citation.title | ELECTRONICS | - |
dc.citation.volume | 12 | - |
dc.citation.number | 23 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스위스 | - |
dc.subject.keywordAuthor | speech technologies | - |
dc.subject.keywordAuthor | call center | - |
dc.subject.keywordAuthor | speech corpus | - |
dc.subject.keywordAuthor | Uzbek language | - |
dc.subject.keywordAuthor | speech-to-text | - |
dc.subject.keywordAuthor | text-to-speech | - |
dc.subject.keywordAuthor | speech recognition | - |
dc.subject.keywordAuthor | speech synthesis | - |
dc.subject.keywordAuthor | IVR | - |
dc.subject.keywordAuthor | public services | - |
dc.subject.keywordPlus | ARTIFICIAL-INTELLIGENCE | - |
dc.subject.keywordPlus | ALEXA | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.