{"id":45398,"date":"2026-10-22T15:12:55","date_gmt":"2026-10-22T13:12:55","guid":{"rendered":"https:\/\/kinit.sk\/?p=45398"},"modified":"2026-10-23T11:14:57","modified_gmt":"2026-10-23T09:14:57","slug":"slovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-modelslovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-model","status":"publish","type":"post","link":"https:\/\/kinit.sk\/sk\/slovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-modelslovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-model\/","title":{"rendered":"Slovak Telekom: Independent benchmark for choosing the right Slovak speech-to-text model"},"content":{"rendered":"<div id=\"\" class=\"element core-list\">\n<ul class=\"wp-block-list\"><div id=\"\" class=\"element core-list-item\">\n<li><strong>Project name:<\/strong> Slovak Speech-to-Text Model Benchmark<\/li>\n<\/div>\n\n<div id=\"\" class=\"element core-list-item\">\n<li><strong>Project\u2019s period<\/strong>: September 2025 to May 2026<\/li>\n<\/div>\n\n<div id=\"\" class=\"element core-list-item\">\n<li><strong>Partner<\/strong>: Slovak Telekom<\/li>\n<\/div><\/ul>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>Call center analysis tools like summarization, topic classification, and sentiment analysis all depend on one thing: a reliable speech-to-text model. But which one should a company choose for Slovak? Until now, there was no way to answer this with data. No benchmark of speech-to-text models existed for the Slovak language, since public leaderboards focus on English or on multilingual datasets where Slovak is largely absent. Without objective evidence, choosing between commercial providers and open-weight models carries significant financial and operational risk.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>The goal of the project was to close this gap: build an independent benchmark of speech-to-text models for Slovak, with a special focus on the telecommunications domain, and give Slovak Telekom a solid evidence base for choosing the right solution.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-heading\">\n<h3 class=\"wp-block-heading\">How we approached it<\/h3>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>Building such a benchmark is out of reach for most individual companies. It requires hundreds of hours of curated Slovak audio with verified transcripts, a fair evaluation methodology, and the infrastructure to run dozens of models over the whole dataset.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>We collected and curated <strong>354 hours of Slovak audio with transcripts<\/strong> across multiple domains, combining public datasets, data provided by Slovak Telekom, and new datasets created at KInIT, including municipal council hearings, read literary texts, and scripted call center dialogues. On this data, we evaluated <strong>more than 20 speech-to-text models<\/strong>, both commercial services and open-weight models, from several perspectives that matter in real applications:<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-list\">\n<ul class=\"wp-block-list\"><div id=\"\" class=\"element core-list-item\">\n<li><strong>Overall transcription accuracy<\/strong> on general and domain-specific Slovak speech.<\/li>\n<\/div>\n\n<div id=\"\" class=\"element core-list-item\">\n<li><strong>Numbers:<\/strong> how reliably models transcribe amounts, dates, and identifiers, measured with dedicated digit-level error metrics.<\/li>\n<\/div>\n\n<div id=\"\" class=\"element core-list-item\">\n<li><strong>Domain terminology:<\/strong> recognition of telco-specific terms, measured with precision and recall for each term.<\/li>\n<\/div>\n\n<div id=\"\" class=\"element core-list-item\">\n<li><strong>Noise robustness:<\/strong> clients call from noisy streets or places with poor signal, so we simulated six types of audio distortion at multiple intensities and measured how each model degrades.<\/li>\n<\/div><\/ul>\n<\/div>\n\n<div id=\"\" class=\"element acf-memberquote\"><section class=\"memberquote \" style=\"background-color: #ebf7f9;\">\n\t<div class=\"wrapper-out\">\n\t\t<div class=\"in cf\">\n\t\t\t<div class=\"inner cf\">\n                                                                    <div class=\"photo Small\">\n                            <img decoding=\"async\" data-src=\"https:\/\/kinit.sk\/wp-content\/uploads\/2026\/10\/Gregor-Viktor-edited.png\" alt=\"Gregor Viktor\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 622px; --smush-placeholder-aspect-ratio: 622\/622;\">\n                        <\/div>\n                                <div class=\"text\">\n                    <h4>\u201cUntil now, anyone choosing a speech-to-text model for Slovak had to rely on accuracy numbers reported by each vendor on their own data. A fair comparison of all models on the same Slovak data is a completely different level of evidence. I am glad we filled this gap, and the benchmark has already opened promising directions for further research.&#8220;<\/h4>                    <p class=\"name\">Viktor Gregor<\/p>                    <p class=\"position\">Research Engineer, KInIT<\/p>                <\/div>\n                        \t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n<\/div>\n\n<div id=\"\" class=\"element core-heading\">\n<h3 class=\"wp-block-heading\">What we delivered<\/h3>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>The main output is a detailed benchmark report that gives Slovak Telekom an objective comparison of available speech-to-text solutions for Slovak. The results serve as a concrete performance baseline that any current or future provider can be measured against, turning vendor selection from a matter of trust into a matter of evidence. The benchmark is also built as a reusable framework: adding a new model requires no methodological changes, so the evaluation stays current as the market evolves.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>The project also opened promising follow-up directions. We proposed a process for labeling Slovak Telekom&#8217;s anonymized call center recordings by combining multiple strong models with human validation on a sample, producing in-domain data at a fraction of the cost of manual transcription. Such data can be used to fine-tune open-weight models for the telco domain and an end-to-end evaluation of the whole analysis pipeline, from audio to insights.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element acf-memberquote\"><section class=\"memberquote \" style=\"background-color: #ebf7f9;\">\n\t<div class=\"wrapper-out\">\n\t\t<div class=\"in cf\">\n\t\t\t<div class=\"inner cf\">\n                                                                    <div class=\"photo Small\">\n                            <img decoding=\"async\" data-src=\"https:\/\/kinit.sk\/wp-content\/uploads\/2026\/10\/telekom_michal_kabac-edited.png\" alt=\"telekom_michal_kabac\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 577px; --smush-placeholder-aspect-ratio: 577\/577;\">\n                        <\/div>\n                                <div class=\"text\">\n                    <h4>\u201cThe benchmark from KInIT gave us an objective view of how speech-to-text technologies actually perform on Slovak, including on data from our own domain. It is a solid basis for our decisions about which technology to use in analyzing customer conversations and where to invest next.&#8220;<\/h4>                    <p class=\"name\">Michal Kab\u00e1\u010d<\/p>                    <p class=\"position\">Data scientist Expert, Slovak Telekom<\/p>                <\/div>\n                        \t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n<\/div>\n\n<div id=\"\" class=\"element core-columns\">\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\"><div id=\"\" class=\"element core-column\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><\/div>\n<\/div>\n\n<div id=\"\" class=\"element core-column\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><div id=\"\" class=\"element core-image\">\n<figure class=\"wp-block-image size-full is-resized\"><img decoding=\"async\" width=\"360\" height=\"360\" data-src=\"https:\/\/kinit.sk\/wp-content\/uploads\/2026\/10\/T_logo_carrier_surface_rgb_n-e1792668690745.png\" alt=\"\" class=\"wp-image-45389 lazyload\" style=\"--smush-placeholder-width: 360px; --smush-placeholder-aspect-ratio: 360\/360;width:159px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/figure>\n<\/div><\/div>\n<\/div>\n\n<div id=\"\" class=\"element core-column\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><\/div>\n<\/div><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Call center analysis tools like summarization, topic classification, and sentiment analysis all depend on one thing: a reliable speech-to-text model. But which one should a company choose for Slovak? Until&#8230;<\/p>\n","protected":false},"author":43,"featured_media":45437,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[83,542],"tags":[515,548],"class_list":["post-45398","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-sk","category-2026-sk","tag-success-story-sk","tag-speech-to-text-sk"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Slovak Telekom: Independent benchmark for choosing the right Slovak speech-to-text model - KInIT<\/title>\n<meta name=\"description\" content=\"Call center analysis tools like summarization, topic classification, and sentiment analysis all depend on one thing: a reliable...\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/kinit.sk\/sk\/slovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-modelslovak-telekom-independent-benchmark-for-choosing-the-right-slovak-speech-to-text-model\/\" \/>\n<meta property=\"og:locale\" content=\"sk_SK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Slovak Telekom: Independent benchmark for choosing the right Slovak speech-to-text model - 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