The corpus contains recordings by the native speakers of the North Levantine Arabic (apc) acquired during 2020, 2021, and 2023 in Prague, Paris, Kabardia, and St. Petersburg. Altogether, there were 13 speakers (9 male and 4 female, aged 1x 15-20, 7x 20-30, 4x 30-40, and 1x 40-50).
The recordings contain both monologues and dialogues on the topics of everyday life (health, education, family life, sports, culture) as well as information on both host countries (living abroad) and country of origin (Syria traditions, education system, etc.). Both types are spontaneous, the participants were given only the general subject and talked on the topic or discussed it freely. The transcription and translation team consisted of students of Arabic at Charles University, with an additional quality check provided by the native speakers of the dialect.
The textual data is split between the (parallel) transcriptions (.apc) and translations (.eng), with one segment per line. The additional .yaml file provides mapping to the corresponding audio file (with the duration and offset in the "%S.%03d" format, i.e., seconds and milliseconds) and a unique speaker ID.
The audio data is shared in the 48kHz .wav format, with dialogues and monologues in separate folders. All of the recordings are mono, with a single channel. For dialogues, there is a separate file for each speaker, e.g., "Tar_13052022_Czechia-01.wav" and "Tar_13052022_Czechia-02.wav".
The data provided in this repository corresponds to the validation split of the dialectal Arabic to English shared task hosted at the 21st edition of the International Conference on Spoken Language Translation, i.e., IWSLT 2024.
The corpus contains recordings by the native speakers of the North Levantine Arabic (apc) acquired during 2020, 2021, and 2023 in Prague, Paris, Kabardia, and St. Petersburg. Altogether, there were 13 speakers (9 male and 4 female, aged 1x 15-20, 7x 20-30, 4x 30-40, and 1x 40-50).
The recordings contain both monologues and dialogues on the topics of everyday life (health, education, family life, sports, culture) as well as information on both host countries (living abroad) and country of origin (Syria traditions, education system, etc.). Both types are spontaneous, the participants were given only the general subject and talked on the topic or discussed it freely. The transcription and translation team consisted of students of Arabic at Charles University, with an additional quality check provided by the native speakers of the dialect.
The textual data is split between the (parallel) transcriptions (.apc) and translations (.eng), with one segment per line. The additional .yaml file provides mapping to the corresponding audio file (with the duration and offset in the "%S.%03d" format, i.e., seconds and milliseconds) and a unique speaker ID.
The audio data is shared in the 48kHz .wav format, with dialogues and monologues in separate folders. All of the recordings are mono, with a single channel. For dialogues, there is a separate file for each speaker, e.g., "16072022_Family-01.wav" and "16072022_Family-02.wav".
The data provided in this repository corresponds to the test split of the dialectal Arabic to English shared task hosted at the 21st edition of the International Conference on Spoken Language Translation, i.e., IWSLT 2024.
UMC 0.1 Czech-English-Russian is a multilingual parallel corpus of texts in Czech, Russian and English languages with automatic pairwise sentence alignments. The primary aim of UMC is to extend the set of languages covered by the corpus CzEng mainly for the purposes of machine translation.
All the texts were downloaded from a single source — The Project Syndicate (Copyright: Project Syndicate 1995-2008), which contains a huge collection of high-quality news articles and commentaries. We were given the permission to use the texts for research and non-commercial purposes. and FP6-IST-5-034291-STP (EuroMatrix)
The goal of the Uniform Meaning Representation (UMR) project is to design a meaning representation that can be used to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries. UMR is intended to be scalable, learnable, and cross-linguistically plausible. It is designed to support both lexical and logical inference.
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). This is the second release of UD Treebanks, Version 1.1.
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
This release is special in that the treebanks will be used as training/development data in the CoNLL 2017 shared task (http://universaldependencies.org/conll17/). Test data are not released, except for the few treebanks that do not take part in the shared task. 64 treebanks will be in the shared task, and they correspond to the following 45 languages: Ancient Greek, Arabic, Basque, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Gothic, Greek, Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Kazakh, Korean, Latin, Latvian, Norwegian, Old Church Slavonic, Persian, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Spanish, Swedish, Turkish, Ukrainian, Urdu, Uyghur and Vietnamese.
This release fixes a bug in http://hdl.handle.net/11234/1-1976. Changed files: ud-tools-v2.0.tgz (conllu_to_text.pl, conllu_to_conllx.pl; added text_without_spaces.pl), ud-treebanks-conll2017.tgz (fi_ftb-ud-train.txt, he-ud-train.txt, it-ud-train.txt, pt_br-ud-train.txt, es-ud-train.txt) and ud-treebanks-v2.0.tgz (fi_ftb-ud-train.txt, he-ud-train.txt, it-ud-train.txt, pt_br-ud-train.txt, es-ud-train.txt, ar_nyuad-ud-dev.txt, ar_nyuad-ud-test.txt, ar_nyuad-ud-train.txt, cop-ud-dev.txt, cop-ud-test.txt, cop-ud-train.txt, sa-ud-dev.txt, sa-ud-test.txt, sa-ud-train.txt).