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Keybot 146 Résultats  dannychoo.com
  Málföng  
Hægt er að sækja Framburðarorðabókina hér á vefnum. Væntanlegir notendur þurfa að skrá sig og samþykkja notkunarskilmála. Textarnir eru aðgengilegir með CC BY 3.0 leyfi.
You can Download the Pronunciation Dictionary. Prospective users must register and accept the terms and conditions. The texts are accessible through a CC BY 3.0 licence.
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Hægt er að sækja Mynstur og setningar hér á vefnum. Væntanlegir notendur þurfa að skrá sig og samþykkja notkunarskilmála. Textarnir eru aðgengilegir með CC BY 3.0 leyfi.
You can Download Patterns and Sentences. Prospective users must register and accept the terms and conditions. The texts are accessible through a CC BY 3.0 licence.
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Meðal umfjöllunarefna í umræðutímunum eru fjárlög, skattamál, vatnalög, orkumál, skólamál og samgöngur, auk þess sem finna má fundarstjórn forseta.
Among the topics of the discussion sessions are the government budget, taxation, water laws, energy, schools and transportation.
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1Þegar birtar eru niðurstöður sem eru fengnar með því að nota gögn Gullstaðalins vinsamlegast vitnið í:
1When publishing results based on the texts in MIM-GOLD please refer to:
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Skrárnar "The_Broadcast_News_RUV-1_Corpus/*.wav" eru bútaðar hljóðskrár.
The files "The_Broadcast_News_RUV-1_Corpus/*.wav" are segmented wave files.
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Alþingisumræður er málheild með íslensku talmáli. Í málheildinni eru ræður frá Alþingi Íslendinga, alls rúmir tuttugu klukkutímar af upptökum ásamt umritun þeirra í texta. Hljóð- og textaskrár eru samstilltar.
Alþingisumræður (Parliament Speech Corpus) is an Icelandic spoken language corpus that contains twenty hours of speeches from the Icelandic Parliament, in synchronized text- and sound files.
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Samhliða var gengið frá lýsigögnum þar sem skráðar eru kerfisbundið upplýsingar um upptökurnar (dagsetning, lengd, umræðuefni, fjöldi þátttakenda o.fl.) og málhafana (aldur, kyn, uppruni o.fl.).
In addition metadata containing information about the recordings (data, length, subject, number of participants etc.) and the speakers (age, gender, origin, etc.) was compiled.
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1Þegar birtar eru niðurstöður sem eru fengnar með því að nota gögn Málróms vinsamlegast vitnið í:
1When publishing results based on data in the Málrómur database please refer to: :
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Eftirfarandi upplýsingar eru um málhafana, aldur þeirra, stað í upphaflegu DAT-upptökunum og línurnar sem þeir lásu.
Here is information about the readers, their age, the records position on the original DAT tape, and the lines read.
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1Þegar birtar eru niðurstöður sem eru fengnar með því að nota gögn Gullstaðalins vinsamlegast vitnið í:
1When publishing results based on the texts in MIM-GOLD please refer to:
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Alþingisumræður er málheild með íslensku talmáli. Í málheildinni eru ræður frá Alþingi Íslendinga, alls rúmir tuttugu klukkutímar af upptökum ásamt umritun þeirra í texta. Hljóð- og textaskrár eru samstilltar.
Alþingisumræður (Parliament Speech Corpus) is an Icelandic spoken language corpus that contains twenty hours of speeches from the Icelandic Parliament, in synchronized text- and sound files.
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Þegar mörkun var lokið voru mörk í þeim hluta texta Sturlungu sem eru í þjálfunarsafninu færð í rétt horf miðað við þær skrár sem höfðu verið leiðréttar áður.
After tagging was completed tags in the part of the Sturlunga texts that are also a part of the training corpus were restored to the corrected value.
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Fornmálstextarnir eru aðgengilegir til notkunar á tvenns konar hátt:
The texts of the Saga Corpus are available for use in two different ways:
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1Þegar birtar eru niðurstöður sem eru fengnar með því að nota gögn Málróms vinsamlegast vitnið í:
1When publishing results based on data in the Málrómur database please refer to: :
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Í umritunarskránum eru alls rúmlega 180 þúsund lesmálsorð.
In total, the transcription files consist of over 180 thousand running words.
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Í öðrum áfanga veturinn 2016–2017 hlustuðu tveir rannsóknarmenn á óstytta útgáfu af þeim raddsýnum sem var hafnað og flokkuðu þau nánar. Af þeim reyndust 8.548 vera í lagi. Samtals er því talið að 108.568 raddsýni séu í lagi og eru þau aðgengileg á þessari síðu.
In total 127,286 voice samples were recorded, failed recordings were 5,401 resulting in 121,885 voice samples that were evaluated. Before the verification process started new sound files were created by trimming long periods of silence at the beginning and end of the recordings. The total duration of the untrimmed files is about 152 hours but was reduced to about 90 hours. During this process 2,795 files were identified as silent. In the first stage of the verification process therefore 119,090 voice samples were evaluated. 100,020 recordings were accepted as correct, and 19,070 were rejected. During the second stage in the winter of 2016–2017 two evaluators listened to untrimmed versions of the 19,070 recordings that were rejected in stage one and classified them further. Of these samples 8,548 were classified as correct. In total it is considered that 108,568 voice samples are good and are available through this webpage.
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Í Risamálheildinni (RMH) má finna um 1300 milljónir lesmálsorða af textum sem eru geymdir í stöðluðu sniði í rafrænu formi. Orð í textunum eru greind málfræðilega og hverjum texta fylgja bókfræðilegar upplýsingar um verkið sem textinn er úr.
The Icelandic Gigaword corpus (IGC) consists of about 1300 million running words of text. The Gigaword corpus is a tagged corpus which means that each running word is accompanied by a morphosyntactic tag and lemma and each text is accompanied by bibliographic information. The corpus is intended for linguistic research and for use in Language Technology projects.
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1Þegar birtar eru niðurstöður rannsókna sem gerðar eru með aðstoð RMH skal hennar getið sem heimildar: Risamálheild. Verkefnisstjórn: Eiríkur Rögnvaldsson, Sigrún Helgadóttir og Steinþór Steingrímsson.
1When publishing results based on the texts in the Icelandic Gigaword Corpus please refer to: The Icelandic Gigaword Corpus. Project management: Eiríkur Rögnvaldsson, Sigrún Helgadóttir and Steinþór Steingrímsson. The Arni Magnússon Institute for Icelandic Studies. Downloaded [DATE] from http://www.malfong.is. The same applies to the release of any language technology tools that have used IGC.
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Í Risamálheildinni (RMH) má finna um 1300 milljónir lesmálsorða af textum sem eru geymdir í stöðluðu sniði í rafrænu formi. Orð í textunum eru greind málfræðilega og hverjum texta fylgja bókfræðilegar upplýsingar um verkið sem textinn er úr.
The Icelandic Gigaword corpus (IGC) consists of about 1300 million running words of text. The Gigaword corpus is a tagged corpus which means that each running word is accompanied by a morphosyntactic tag and lemma and each text is accompanied by bibliographic information. The corpus is intended for linguistic research and for use in Language Technology projects.
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Væntanlegir notendur þurfa að samþykkja sérstakt notkunarleyfi fyrir RMH1 og CC BY leyfi fyrir RMH2. Textarnir eru aðgengilegir í sérstöku xml-sniði, TEI P5, sem er skilgreint af TEI (Text Encoding Initiative).
The corpus will be available in two ways. Firstly the corpus will be available for search where the tags (linguistic annotation) can be used to define the search more accurately. The search gives a KWIC index and information about the source of each text example. The search interface is based on the Swedish search interface Korp.
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Íslenska Risamálheildin er safn um 1300 milljóna lesmálsorða af texta. Hluti textanna eru opinberir textar (t.d. Alþingisræður sem ná aftur til ársins 1907, lagatexti, dómar). Einnig fengust stór textasöfn frá ýmsum fjölmiðlum og ýmsir textar úr textasafni Árnastofnunar.
The Icelandic Gigaword corpus consists of about 1300 million running words of text. Part of the corpus texts are official texts (e.g. parliamentary speeches as far back as 1907, law text, adjudications). The corpus also contains big text collections from news media and various texts from the text collection of the Árni Magnússon Institute for Icelandic Studies. The Gigaword corpus is a tagged corpus as described above. The corpus was compiled during the years 2015 to 2017 at the Árni Magnússon Institute for Icelandic Studies. Only texts available in digital form were collected.
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Markamengið sem er notað er það sem var þróað fyrir gerð Íslenskrar orðtíðnibókar með nokkrum breytingum. Sérnöfn eru ekki greind í mannanöfn, staðarnöfn og önnur nöfn. Markinu v var bætt við fyrir vefföng og tölvupóstföng.
The corpus was tagged by automatic means. The texts in IGC were divided into sentences and running words and then tagged and lemmatized. IceNLP was used to divide the text into sentences and running words. Tagging was performed with IceStagger2. Lemmatization was performed with the lemmatizer Nefnir3. Tags and lemmas are not manually corrected.
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Markamengið sem er notað er það sem var þróað fyrir gerð Íslenskrar orðtíðnibókar með nokkrum breytingum. Sérnöfn eru ekki greind í mannanöfn, staðarnöfn og önnur nöfn. Markinu v var bætt við fyrir vefföng og tölvupóstföng.
The corpus was tagged by automatic means. The texts in IGC were divided into sentences and running words and then tagged and lemmatized. IceNLP was used to divide the text into sentences and running words. Tagging was performed with IceStagger2. Lemmatization was performed with the lemmatizer Nefnir3. Tags and lemmas are not manually corrected.
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Með markaðri málheild (e. tagged corpus) er átt við safn fjölbreyttra texta sem eru geymdir í stöðluðu sniði í rafrænu formi. Til þess að textarnir verði sem gagnlegastir við málrannsóknir eru þeir greindir á margvíslegan hátt.
A tagged corpus is a collection of electronic texts in a standard format. The texts are analyzed in various ways to make them suitable for linguistic research and Language Technology projects. Each running word in the text is followed by a tag which shows part-of-speech and often also morphosyntactic elements like case, number and gender for nominals and person, number and tense for verbs. Each running word is also accompanied by a lemma, e.g. nominals in the nominative singular and the infinitive for verbs. Each text is also accompanied by metadata (bibliographic information for published texts).
  Málföng  
Með markaðri málheild (e. tagged corpus) er átt við safn fjölbreyttra texta sem eru geymdir í stöðluðu sniði í rafrænu formi. Til þess að textarnir verði sem gagnlegastir við málrannsóknir eru þeir greindir á margvíslegan hátt.
A tagged corpus is a collection of electronic texts in a standard format. The texts are analyzed in various ways to make them suitable for linguistic research and Language Technology projects. Each running word in the text is followed by a tag which shows part-of-speech and often also morphosyntactic elements like case, number and gender for nominals and person, number and tense for verbs. Each running word is also accompanied by a lemma, e.g. nominals in the nominative singular and the infinitive for verbs. Each text is also accompanied by metadata (bibliographic information for published texts).
  Málföng  
Markamengið sem er notað er það sem var þróað fyrir gerð Íslenskrar orðtíðnibókar með nokkrum breytingum. Sérnöfn eru ekki greind í mannanöfn, staðarnöfn og önnur nöfn. Markinu v var bætt við fyrir vefföng og tölvupóstföng.
The corpus was tagged by automatic means. The texts in IGC were divided into sentences and running words and then tagged and lemmatized. IceNLP was used to divide the text into sentences and running words. Tagging was performed with IceStagger2. Lemmatization was performed with the lemmatizer Nefnir3. Tags and lemmas are not manually corrected.
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Gögn verkefnisins eru vistuð í tveimur aðgreindum gagnagrunnum. Grunnurinn Þesárus geymir allan efniviðinn. Valinn hluti gagnanna er afmarkaður og birtur á vefsíðunni ordanet.is.
The database Þesárus contains all the data of the project. Selected part of the data is then delimited and published on the website ordanet.is as a separate entity.
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Fletturnar eru merkingarlega einræðar og það hefur mótandi áhrif á lýsingu merkingarvenslanna. Einræðingin hefur m.a. víðtæk áhrif á flettumyndir sagna þar sem rökliðirnir hverju sinni eru hluti af flettustrengnum og sagnasambönd af ýmsu tagi fá sjálfstæða stöðu innan flettulistans.
The lemmas are semantically unambiguous which has profound impact on the description of the semantic relations. To name an example, the arguments of verbs are taken to be a part of the lemma, and verbal combinations of various kinds have independent status within the lemma list.
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Fletturnar eru merkingarlega einræðar og það hefur mótandi áhrif á lýsingu merkingarvenslanna. Einræðingin hefur m.a. víðtæk áhrif á flettumyndir sagna þar sem rökliðirnir hverju sinni eru hluti af flettustrengnum og sagnasambönd af ýmsu tagi fá sjálfstæða stöðu innan flettulistans.
The lemmas are semantically unambiguous which has profound impact on the description of the semantic relations. To name an example, the arguments of verbs are taken to be a part of the lemma, and verbal combinations of various kinds have independent status within the lemma list.
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Merkingarvenslin sem um ræðir eru af ólíku tagi. Skýrustu og nálægustu venslin eru fólgin í samheitum og andheitum en samheitavenslin eru misjafnlega náin og sá greinarmunur er að nokkru leyti auðkenndur með því að greina á milli samheita og skyldheita.
The semantic relations in question are of various kinds. The clearest and closest relations constitute synonyms and antonyms but the synonym relations vary in closeness. The difference is partially identified by distinguishing between synonyms and near-synonyms. For estimating the relations, the emphasis is laid on the evidence of the material, where the goal is to obtain numeric evidence of semantic proximity and the semantic relatedness of the words compared. The analysis also returns semantically homologous vocabulary which is further sorted and placed under particular concepts and semantic fields.
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Merkingarvenslin sem um ræðir eru af ólíku tagi. Skýrustu og nálægustu venslin eru fólgin í samheitum og andheitum en samheitavenslin eru misjafnlega náin og sá greinarmunur er að nokkru leyti auðkenndur með því að greina á milli samheita og skyldheita.
The semantic relations in question are of various kinds. The clearest and closest relations constitute synonyms and antonyms but the synonym relations vary in closeness. The difference is partially identified by distinguishing between synonyms and near-synonyms. For estimating the relations, the emphasis is laid on the evidence of the material, where the goal is to obtain numeric evidence of semantic proximity and the semantic relatedness of the words compared. The analysis also returns semantically homologous vocabulary which is further sorted and placed under particular concepts and semantic fields.
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2. Sækja textana. Textarnir eru einnig aðgengilegir í sérstöku xml-sniði sem er skilgreint af TEI (Text Encoding Initiative). Bókfræðilegar upplýsingar fylgja öllum textum. Væntanlegir notendur þurfa að skrá sig og samþykkja sérstakt notkunarleyfi.
2. Download. The texts are available in a special xml-format that is defined by TEI (Text Encoding Initiative). Bibliographical information is included with all the texts. Prospective users must register and accept the terms and conditions of a proprietary user license.
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Textar orðtíðnibókarinnar eru aðgengilegir til notkunar á þrenns konar vegu:
The texts of the IFD are available for use in three different ways:
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The_Jensson_Corpus/jensson.phoneme.dictionary - öll skilgreind fónem í íslensku sem notuð eru í málheildinni.
The_Jensson_Corpus/jensson.phoneme.dictionary - all defined phonemes in Icelandic used in the corpus.
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