Toward Real-Time Medical IVR in Latvian: Evaluation Framework and Comparative Analysis of STT and TTS Models.

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Title: Toward Real-Time Medical IVR in Latvian: Evaluation Framework and Comparative Analysis of STT and TTS Models.
Authors: Petrovica-Klavina, Sintija1 sintija.petrovica-klavina@rtu.lv, Erins, Ingars1 ingars.erins@rtu.lv, Kirsteins, Roberts2 roberts.kirsteins@tet.lv, Meijers, Ints2 ints.meijers@tet.lv, Aunina-Kirmuska, Biruta Eliza2 eliza.aunina@tet.lv
Source: Complex Systems Informatics & Modeling Quarterly. Jun/Jul2026, Issue 47, p105-127. 23p.
Subjects: Interactive voice response (Telecommunication), Real-time computing, Evaluation methodology, Language & languages, Health care industry, Low-resource languages, Text-to-speech software
Abstract: This article investigates state-of-the-art speech-to-text (STT) and textto-speech (TTS) technologies for the development of a conversational interactive voice response (IVR) solution in the Latvian medical domain. The study addresses challenges associated with low-resource languages, domain-specific medical terminology, real-time interaction, and sensitive data processing. A requirementdriven evaluation framework is proposed that integrates linguistic and domain accuracy, architectural and deployment suitability, real-time performance, scalability, and regulatory considerations relevant to healthcare environments. Based on evidence reported in scientific literature, model documentation, and publicly available repositories, candidate STT and TTS models with Latvian support or adaptation potential are comparatively assessed against these requirements. Rather than providing a standardized experimental benchmark, the analysis identifies architectures and models whose documented characteristics appear most closely aligned with the operational requirements of real-time Latvian medical IVR deployment. The study provides a structured basis for candidate model selection and defines the metrics and deployment conditions to be addressed in subsequent common-condition empirical evaluation and clinical validation. [ABSTRACT FROM AUTHOR]
Copyright of Complex Systems Informatics & Modeling Quarterly is the property of RTU Publishing House and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Complex+Systems+Informatics+%26+Modeling+Quarterly%22">Complex Systems Informatics & Modeling Quarterly</searchLink>. Jun/Jul2026, Issue 47, p105-127. 23p.
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  Data: <searchLink fieldCode="DE" term="%22Interactive+voice+response+%28Telecommunication%29%22">Interactive voice response (Telecommunication)</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Language+%26+languages%22">Language & languages</searchLink><br /><searchLink fieldCode="DE" term="%22Health+care+industry%22">Health care industry</searchLink><br /><searchLink fieldCode="DE" term="%22Low-resource+languages%22">Low-resource languages</searchLink><br /><searchLink fieldCode="DE" term="%22Text-to-speech+software%22">Text-to-speech software</searchLink>
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  Data: This article investigates state-of-the-art speech-to-text (STT) and textto-speech (TTS) technologies for the development of a conversational interactive voice response (IVR) solution in the Latvian medical domain. The study addresses challenges associated with low-resource languages, domain-specific medical terminology, real-time interaction, and sensitive data processing. A requirementdriven evaluation framework is proposed that integrates linguistic and domain accuracy, architectural and deployment suitability, real-time performance, scalability, and regulatory considerations relevant to healthcare environments. Based on evidence reported in scientific literature, model documentation, and publicly available repositories, candidate STT and TTS models with Latvian support or adaptation potential are comparatively assessed against these requirements. Rather than providing a standardized experimental benchmark, the analysis identifies architectures and models whose documented characteristics appear most closely aligned with the operational requirements of real-time Latvian medical IVR deployment. The study provides a structured basis for candidate model selection and defines the metrics and deployment conditions to be addressed in subsequent common-condition empirical evaluation and clinical validation. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Complex Systems Informatics & Modeling Quarterly is the property of RTU Publishing House and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.7250/csimq.2026-47.05
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      – SubjectFull: Real-time computing
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      – SubjectFull: Evaluation methodology
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      – SubjectFull: Low-resource languages
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      – SubjectFull: Text-to-speech software
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      – TitleFull: Toward Real-Time Medical IVR in Latvian: Evaluation Framework and Comparative Analysis of STT and TTS Models.
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            NameFull: Petrovica-Klavina, Sintija
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              M: 06
              Text: Jun/Jul2026
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              Y: 2026
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