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However, having poor results for the Swedish text, which is widely represented in the collection is not satisfactory. In this work, we add a small amount of Swedish training data to our Finnish data sets and train the models using Ocropus software.
All three data sets consist of manually transcribed lines of text. The DIGI data set contains approximately 12, random lines of Finnish, mostly fraktur text a small amount of text is written in Antiqua. Digi and Swedish lines were picked randomly from the entire corpus, while Natlib lines were extracted from random pages of text.
The results show that with already a small amount of additional Swedish data we get a big improvement on the Swedish test set With a character accuracy rate of While improvement on the Swedish test set was expected, it was not obvious that the Finnish test results would increase. It seems that the Digi set is small enough that adding more versatile font information to the training data Swedish texts are more often written in Antiqua benefits the Finnish model as well.
Additionally, Finnish texts contain Swedish names and places, which might be better recognized after the addition of Swedish information. However, the Natlib training set is too big and too specific to be largely influenced by our small addition of extra data. Today national archives contain what might seem to be an unmanageable quantity of data. Data of this sort is often referred to as found data, i. These data are in many cases more valuable compared to data collected in a controlled setting as they provide for higher ecological validity.
We propose an explorative approach with the aim of utilising large amounts of audio data. At this stage, we have experimented with many different types of audio, mostly focusing on speech, and the results are promising. Additionally, he has written several works for the stage in French.
To this end, a relational database collecting and interlinking several types of entities context quotes, foreign language parts of quotes, individual words, foreign and German lemmas was built and all relevant quotes from the stage texts have been collected. The instrument for the analysis of this corpus was created on the bases of transcripts collected from parliamentary sessions. It offers a convenient set of tools that can be used for parliamentary discourse research addressing the research of individual sessions, parliamentary term, parties, personalities, age, or gender speeches.
Texts are automatically tokenized, lemmatized and morphologically analyzed and tagged using CMM based tagger. Syntactic dependencies are inferred by neural transition-based dependency parser trained on Latvian Universal Dependencies corpus version 2. The research work in the cabinet is aimed at obtaining concordances and acquiring commonly used word combinations. The program also allows you to see the name of the neighborhood, in the context of the use of a particular word, which is essential for defining word connections and typical word combinations. The possibilities of the Saeima debate corpus are examined in these four research works with application of critical discourse analysis : 1.
Physicians of Latvian parliament use the same discursive structure of language, which is used for communication with a patient. Politicians resist the initiative of environmental activists to abandon the use of wildlife in a circus. They argue their view in media, referring to the national tradition, but in the analysis parliamentary speeches, the word "circus" is used with contempt. In the parliamentary discourse the concept of state is vague.
However, it is often compared to the parents, mother, or owner, attributing paternal function. In parliamentary speeches during a single term, it was established that the word "sick" is rarely used for its common meaning, instead - for offensive intonation. The notion of information is only formal here, i. A definition of information density is elaborated involving informativity a relative measure of semantic and pragmatic information per clause following .
In computational linguistics, one of the most common characteristics employed to detect information-dense texts is lexical density. This presentation provides a part of the methodology proposed for automatic analysis of information density based on lexical and syntactic levels of language. The methodology was developed by analysing two corpora compiled from the texts of two academic genres - research papers 3 running words and their abstracts 85 running words.
Such analysis proposed that lexical density depends strongly on the form of texts. In other words, lexical level of text is related with syntactic one, i. Thus the first stage of the research suggested a further direction for the analysis: while information density is seen as too complex to measure globally, a study of both lexical and syntactic features allows a comparison of information density between different texts or different text genres.
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Information density in French and Dagara folktales: a corpus-based analysis of linguistic marking and cognitive processing. Doctoral thesis. The poster discusses the possibilities given by application of phylogenetic analysis in textual scholarship. It has been long recognized in the literature, that there are clear similarities between theoretical assumptions of cladistics and stemmatics Howe et al.
ocnilecca.tk This method of data collection with aim of revealing the relationships between the manuscripts is, however, time consuming. It requires a remarkable amount of manual collation and annotation of texts. This poster presents an attempt to automatize this process.