{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T21:51:06Z","timestamp":1740174666197,"version":"3.37.3"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T00:00:00Z","timestamp":1663545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Language identification is a great challenge in language engineering, which arises along with the tasks of speech recognition, machine translation, cross-language information retrieval, intelligent dialogue system creation, etc. The presented article introduces the intelligent language identification technology, which is based on speech recognition and statistical methods of spectrogram analysis. The approach to the automatic identification of the spoken language sample uploaded to the system, in particular from video streaming services such as YouTube, is put forward. The article focuses on the automatic identification of spoken language, taking into account several speech recognition solutions for correct or incorrect speech recognition and its conversion into correct or incorrect text. The obtained algorithm is demonstrated in the Ukrainian and Russian languages. The identification quality of the language of an utterance, which lasts &amp;gt;30 s is almost 100%, and for the utterance of a duration of 30 s, the quality is 98%, and for the 5-s utterance, it reaches 89.6%. In addition to that, the system performance is contingent on the streaming speed, so it is a real-time system.<\/jats:p>","DOI":"10.1093\/llc\/fqac052","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T10:45:26Z","timestamp":1663670726000},"page":"586-595","source":"Crossref","is-referenced-by-count":0,"title":["Spoken language identification based on the transcript analysis"],"prefix":"10.1093","volume":"38","author":[{"given":"Dmytro V","family":"Lande","sequence":"first","affiliation":[{"name":"Institute of Information Recording Problems , Ky\u00efv, Ukraine"},{"name":"National Technical University of Ukraine \u201cIgor Sikorsky Ky\u00efv Polytechnic Institute\u201d , Ky\u00efv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olegh O","family":"Dmytrenko","sequence":"additional","affiliation":[{"name":"Institute of Information Recording Problems , Ky\u00efv, Ukraine"},{"name":"National Technical University of Ukraine \u201cIgor Sikorsky Ky\u00efv Polytechnic Institute\u201d , Ky\u00efv, Ukraine"},{"name":"Institute of Problems of Artificial Intelligence , Ky\u00efv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anatolij I","family":"Shevchenko","sequence":"additional","affiliation":[{"name":"Institute of Problems of Artificial Intelligence , Ky\u00efv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mykyta S","family":"Klymenko","sequence":"additional","affiliation":[{"name":"Institute of Problems of Artificial Intelligence , Ky\u00efv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0772-7950","authenticated-orcid":false,"given":"Maksym O","family":"Vakulenko","sequence":"additional","affiliation":[{"name":"Institute of Problems of Artificial Intelligence , Ky\u00efv, Ukraine"},{"name":"State Scientific and Technical Library of Ukraine , Ky\u00efv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,9,19]]},"reference":[{"author":"Alpha Cephei","key":"2023053108330417900_fqac052-B1"},{"author":"Alpha Cephei","key":"2023053108330417900_fqac052-B2"},{"year":"2015","author":"Amodei","key":"2023053108330417900_fqac052-B3"},{"issue":"4","key":"2023053108330417900_fqac052-B4","first-page":"4243","article-title":"Spoken language identification system using MFCC features and Gaussian Mixture Model for Tamil and Telugu Languages","volume":"6","author":"Athiyaa","year":"2019","journal-title":"International Research Journal of Engineering and Technology (IRJET)"},{"volume-title":"Automatic Natural Language Processing and Computational Linguistics","year":"2011","author":"Bolshakova","key":"2023053108330417900_fqac052-B5"},{"volume-title":"Methods for Spoken Language Identification","year":"2017","author":"Boussard","key":"2023053108330417900_fqac052-B6"},{"key":"2023053108330417900_fqac052-B7","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.csl.2005.06.003","article-title":"Support vector machines for speaker and language recognition","volume":"20","author":"Campbell","year":"2006","journal-title":"Computer Speech and Language:"},{"year":"2017","author":"Dauphin","key":"2023053108330417900_fqac052-B8"},{"key":"2023053108330417900_fqac052-B9","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1007\/s10772-018-9526-5","article-title":"Spoken language recognition using a new conditional cascade method to combine acoustic and phonetic results","volume":"21","author":"Firooz","year":"2018","journal-title":"International Journal of Speech Technology"},{"key":"2023053108330417900_fqac052-B10","volume-title":"The Advanced Theory of Statistics","author":"Kendall","year":"1977","edition":"4th edn"},{"key":"2023053108330417900_fqac052-B12","first-page":"65","volume-title":"Applied Linguistics and Linguistic Technology: MegaLing\u20192010: Collection of Research Papers\/NAS of Ukraine, Ukrainian Lingua-Information Fund","author":"Lande","year":"2010"},{"issue":"5","key":"2023053108330417900_fqac052-B13","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.1109\/JPROC.2012.2237151","article-title":"Spoken Language Recognition: From Fundamentals to Practice","volume":"101","author":"Li","journal-title":"Proceedings of the IEEE"},{"author":"MoviePy","key":"2023053108330417900_fqac052-B14"},{"author":"pndurette\/gTTS","key":"2023053108330417900_fqac052-B15"},{"key":"2023053108330417900_fqac052-B16","first-page":"43","volume-title":"PROPOR 2020. 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