In NLP Centre, dividing text into sentences is currently done with
a tool which uses rule-based system. In order to make enough training
data for machine learning, annotators manually split the corpus of contemporary text
CBB.blog (1 million tokens) into sentences.
Each file contains one hundredth of the whole corpus and all data were
processed in parallel by two annotators.
The corpus was created from ten contemporary blogs:
hintzu.otaku.cz
modnipeklo.cz
bloc.cz
aleneprokopova.blogspot.com
blog.aktualne.cz
fuchsova.blog.onaidnes.cz
havlik.blog.idnes.cz
blog.aktualne.centrum.cz
klusak.blogspot.cz
myego.cz/welldone
This corpus contains a variety of works written in Finnish published between 1809 and 1899, such as newspapers, periodicals, almanacs, and decrees.
The corpus contains 8,976,561 words and is available for online browsing.
The classics of Finnish literature corpus contains works by established Finnish fiction writers from the 1880s to the 1930s. The corpus is part of speech tagged and available for online browsing via the concordancer Korp.
Italian emblem books from the Stirling Maxwell Collection (University of Glasgow). Transcribed text and photographi reproducitons. Searchable and browsable online
This is a linguistically unannotated corpus of various historical texts written between 1543 and 1809.
The corpus consists of 3,428,618 words and is available for online browsing.
The corpus contains speech data of 2 Czech native speakers, male and female. The speech is very precisely articulated up to hyper-articulated, and the speech rate is low. The speech data with a highlighted articulation is suitable for teaching foreigners the Czech language, and it can also be used for people with hearing or speech impairment. The recorded sentences can be used either directly, e.g., as a part of educational material, or as source data for building complex educational systems incorporating speech synthesis technology. All recorded sentences were precisely orthographically annotated and phonetically segmented, i.e., split into phones, using modern neural network-based methods.