OLAC Record

Title:Spoken corpus Gos VideoLectures 4.0 (transcription)
Bibliographic Citation:http://hdl.handle.net/11356/1223
Creator:Verdonik, Darinka
Potočnik, Tomaž
Sepesy Maučec, Mirjam
Erjavec, Tomaž
Majhenič, Simona
Žgank, Andrej
Date (W3CDTF):2019-03-27T08:03:42Z
Date Available:2019-03-27T08:03:42Z
Description:Gos VideoLectures is an add-on to the Gos reference corpus of spoken Slovene (http://hdl.handle.net/11356/1040), and covers public academic speech. The Gos VideoLectures corpus contains a selection of public lectures available through the web portal Videolectures.net provided by the Jožef Stefan Institute, and covers 55 lectures and 22 hours of speech. This resource contains only annotated transcriptions of the corpus – audio recordings are available at http://hdl.handle.net/11356/1222. The transcriptions for Gos VideoLectures were done manually and carefully checked. The main guidelines for transcription were those of the Gos corpus (http://www.korpus-gos.net/Support/About). The transcription tool Transcriber 1.5.1 (http://trans.sourceforge.net/en/presentation.php) was used for making transcriptions. It can be also used for reading or exporting transcriptions (.trs files) to different formats. The transcriptions comprise the TRS files with tabular metadata, their conversion to TEI and to vertical file format (as used e.g. by Sketch Engine). Each recording has two TRS files, one with pronunciation-based and the other with the standardised/normalised transcription. The TEI and CWB encodings join these two transcriptions at the token level, with the normalised words being also automatically PoS tagged and lemmatised. The TRS pack also contains files with automatically produced word and phone-level alignment with the speech signal. The corpus can be used for training continuous speech recognition for Slovene language, for phonetic research or any other research of Slovene academic speech.
Identifier (URI):http://hdl.handle.net/11356/1223
Language (ISO639):slv
Publisher:Faculty of Electrical Engineering and Computer Science, University of Maribor
Replaces (URI):http://hdl.handle.net/11356/1190
Rights:Creative Commons - Attribution 4.0 International (CC BY 4.0)
Subject:speech database
spoken corpus
academic speech
speech transcription
speech recognition
Type (DCMI):Text
Type (OLAC):primary_text


Archive:  Slovenian language resource repository CLARIN.SI
Description:  http://www.language-archives.org/archive/clarin.si
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OaiIdentifier:  oai:www.clarin.si:11356/1223
DateStamp:  2019-03-27
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Citation: Verdonik, Darinka; Potočnik, Tomaž; Sepesy Maučec, Mirjam; Erjavec, Tomaž; Majhenič, Simona; Žgank, Andrej. 2019. Faculty of Electrical Engineering and Computer Science, University of Maribor.
Terms: area_Europe country_SI dcmi_Text iso639_slv olac_primary_text

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