- Finnish Vocabulary for English Speakers - 5000 Words
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Finnish Vocabulary for English Speakers - 5000 Words
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This corpus is the main support for teaching and research at our institut. Some of the research activities envisaged against this corpus include the following ones: terminology detection, parallel texts alignment, partial parsing, semi automatic extraction of several levels of linguistic information for building computational systems for example, subcategorization patterns , language variation studies.
Each verb and adjective occurring in the Treebank has been treated as a semantic predicate and the surrounding text has been annotated for arguments and adjuncts of the predicate. The verbs and adjectives have also been tagged with coarse grained senses. A frames file, consisting of one or more frame sets, has been created for each predicate occurring in the Treebank. These files serve as a reference for the annotators and for users of the data.
There are two annotation files. The virginia-verbs. The newswire-verbs. These predicate tokens include all those occurring in over thousand words of the Korean Treebank version 2. It is essentially an electronic corpus of Korean texts annotated with morphological and syntactic information. The original texts for the Korean Treebank 2. Korean Treebank 2.
The annotated corpus can find many uses, including training of morphological analyzers, part-of-speech taggers and syntactic parsers. The goal of MDE is to enable technology that can take raw Speech-to-Text output and refine it into forms that are of more use to humans and to downstream automatic processes. In simple terms, this means the creation of automatic transcripts that are maximally readable.
This readability might be achieved in a number of ways: flagging non-content words like filled pauses and discourse markers for optional removal; marking sections of disfluent speech; and creating boundaries between natural breakpoints in the flow of speech so that each sentence or other meaningful unit of speech might be presented on a separate line within the resulting transcript. Natural capitalization, punctuation and standardized spelling, plus sensible conventions for representing speaker turns and identity are further elements in the readable transcript. Wang Xianzhen. The group chose naval communications as the common task because it naturally includes a great deal of non-native speech and because there were training facilities where data could be collected in several countries.
Speech data was recorded in the Naval transmission training centers of four countries Germany, The Netherlands, United Kingdom, and Canada. The material consists of native and non-native speakers using NATO English procedure between ships and reading from a text. The posts have been: 1 Hand privacy masked; 2 Part-of-speech tagged; and 3 Dialogue-act tagged. All the texts in the corpus have been automatically annotated and contain English translations of most lexemes.
The corpus supports automatic Latin transliteration of search results. It includes the text samples of the Helsinki Corpus of Historical English, which consists of , words of genre balanced text and two extension samples of the same size, balanced for genre in the same way. It is a sister corpus of the Penn-Helsinki Parsed Corpus of Middle English and the two corpora are distributed together. The corpora are genre-balanced and consist of POS-tagged and syntactically annotated text samples, including all of the samples in the Middle and Early Modern English sections of Helsinki Corpus of Historical English 1.
The intend of PMSE is to build a comprehensive toolchain enabling the user a generic work with text corpora - starting with the acquirement of the data, ongoing with statistical computation and data visualization. The corpus is fully searchable online, and the website also contains a description and instructions.
During the second phase up to the representative span of written texts will be extended to other periods of the contemporary language — to the amount of million words and its selected sample will be syntactically annotated. Simultaneously, specific sub-corpora of diachronic and dialectological texts will commence to be built, as well as a terminological and lexicographical database.
Slovak National Corpus is provided primarily to lexicographers dictionary creation , complements grammar and stylistic research grammar and orthographical handbooks; varieties of the national language and their usage in communication. We suppose that it will also find its use at schools preparing of orthography, grammar and style textbooks; teaching Slovak as a foreign language.
Specific sub-corpora of historical and dialectological texts will help to preserve an important part of our cultural heritage in a long-term perspective. It consists of the recordings of speakers of American English from four regions, three age groups and two gender groups, pronouncing isolated words. The recordings were conducted in a sound-attenuated room, and a high-quality microphone was used. Each speaker read a randomized word list consisting of words distinct words appearing 21 times each.
It was collected in and consists of the spoken language of 13 to year-old teenagers from different boroughs of London. The complete corpus, half a million words, has been orthographically transcribed and word-class tagged, and is a constituent of the British National Corpus. These resources can be readily consulted online and also downloaded. In these corpora the semantics of sentences is analyzed as a syntax-lexicon continuum and so the annotation ranges from the lexical level to the sentence level.
Constituents are independently annotated regarding different types of information: semantic role, syntagmatic category, and syntactic and semantic function. The verb phrase is also specified in terms of telicity and dynamism and the sentence is specified regarding topicalization or detopicalization of logical subject, aspectuality, modality and polarity.
All these values converge in order to create sentence meaning. The two SenSem lexicons embrace 1, senses. This description is carried out by means of a definition, the Aktionsart, semantic roles and subcategorization frames with information about frequency and sentence semantics. In the Spanish lexicon, these senses are organized in lemmas, which constitute the headwords for which sentences from a journalistic register and 20 from a literary register have been randomly selected and manually annotated.
The Spanish sentences corresponding to the journalistic register have been translated into Catalan and annotated independently. In the Spanish lexicon, lemmas have been described. These were selected from the most frequent Spanish verbs in an original corpus made up of 13,, words. In the Catalan lexicon, the number of lemmas is higher because the correspondence between Spanish and Catalan verbs is not one-to-one. The two SenSem lexicons embrace 1, senses each, out of which approximately 1, are exemplified in the corpus.
The sense description is carried out by means of a definition, semantic roles, the WordNet synset and the frequency of each sense in the corpus, differentiating between different registers. We also include the Aktionsart. Moreover, each sense is completed with information extracted from the corpora referring to subcategorization frames and their frequency.
In order to describe the patterns, we make use of two levels. In the first level we include the general syntagmatic categories ordered according to the unmarked Spanish word order and we mark those patterns that are pronominal. In the second level these categories are subspecified and semantic roles and syntactic functions are added to the patterns. For each frame we also indicate the sentence semantics that it is associated to, the real order of categories and the adjuncts. Finally, all the sentences of the corpora that exemplify each pattern can be visualized and a graphic shows the annotation of each sentence.
The annotation follows the TimeML 1. The most recent information on TimeML is always available at www. TimeML aims to capture and represent temporal information. Timebank 1.
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Nonmembers may license this data at no cost - please note that a signed copy of our generic nonmember user agreement is required. TS Corpus is a tagged corpus. TS Corpus aims to combine former Turkish computational linguistics studies and other corpus linguistics studies from around the world.
The recordings made for VOICE are keyboarded by trained transcribers and stored as a computerized corpus.
The ELF interactions recorded cover a range of different speech events in terms of domain professional, educational, leisure , function exchanging information, enacting social relationships , and participant roles and relationships acquainted vs. Our data is based on the only large, genre-balanced, up-to-date corpus of American English -- the million word Corpus of Contemporary American English. You can be sure that the words in these lists and in this dictionary - sorted from most to least frequent - are really the most common ones that you will encounter in the real world.
Most are in French with English translations; a few English and Latin proverbs are also included. Universidad de Sevilla. David Harrison in and , for a project funded by a grant from Volkswagen-Stiftung. The dataset contains: comparable summaries, comparable automatic translations, and comparable full documents. All recordings have been aligned with an orthographic transcription and each word has been given a POS tag and a lemma. It provides a range of introductory articles on corpora and corpus-based research, links and conference calls, a glossary of common terms, and some downloadable papers and resources.
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There are some There is a Greek-Armenian lexicon entries , and aligned Armenian-Greek texts. LALT will be updated at regular intervals. Also, LALT easily is able to integrate additional material and welcomes contributions of other scholars. I have been asked about fonts: LALT is written in xml and uses unicode. Any unicode font will be able to read it, provided this font contains the glyphs screen images for Armenian and Greek.
It contains the electronic transcription and edition of some of the most important dictionaries from the 17th and 18th centuries.