dc.contributor.author | Zemánek, Petr |
dc.contributor.author | Pospíšil, Adam |
dc.contributor.author | Sellat, Hashem |
dc.contributor.author | Krubiński, Mateusz |
dc.contributor.author | Pecina, Pavel |
dc.date.accessioned | 2024-06-10T08:56:37Z |
dc.date.available | 2024-06-10T08:56:37Z |
dc.date.issued | 2023 |
dc.identifier.uri | http://hdl.handle.net/11234/1-5518 |
dc.description | 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. |
dc.language.iso | apc |
dc.language.iso | eng |
dc.publisher | Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL) |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/870930 |
dc.rights | Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ |
dc.subject | speech corpus |
dc.subject | speech recognition |
dc.subject | speech-to-text translation |
dc.subject | machine translation |
dc.subject | multilingual |
dc.subject | Arabic |
dc.subject | Arabic Corpus |
dc.subject | north levantine |
dc.title | UFAL Speech Corpus of North Levantine Arabic 1.0 - Part 1 |
dc.type | corpus |
metashare.ResourceInfo#ContentInfo.mediaType | audio |
dc.rights.label | PUB |
has.files | yes |
branding | LINDAT / CLARIAH-CZ |
contact.person | Pavel Pecina pecina@ufal.mff.cuni.cz Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL) |
sponsor | European Union EC/H2020/870930 WELCOME - Multiple Intelligent Conversation Agent Services for Reception, Management and Integration of Third Country Nationals in the EU euFunds info:eu-repo/grantAgreement/EC/H2020/870930 |
size.info | 152 minutes |
files.size | 875274515 |
files.count | 4 |
Files in this item
Download all files in item (834.73 MB)This item is
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- Name
- dev2024.eng
- Size
- 84.08 KB
- Format
- Unknown
- Description
- Speech translation to eng
- MD5
- c726d877a4abb430323609492df6574c
- Name
- dev2024.yaml
- Size
- 110.33 KB
- Format
- Unknown
- Description
- Audio-to-text segment mapping
- MD5
- 5bb2603cc25e326a87e3f586dc7aa01a
- Name
- dev2024.apc
- Size
- 113.6 KB
- Format
- Unknown
- Description
- Speech transcription to apc
- MD5
- 6cc17f60993f87235dc0383d377bced4
- Name
- dev2024_wav.zip
- Size
- 834.43 MB
- Format
- application/zip
- Description
- Audio files
- MD5
- 63e4279f57982ee845d31f61d840e5ac
- Audio-Dialogues
- Tar_13052022_Czechia-01.wav177 MB
- Tar_13052022_Food-01.wav116 MB
- Tar_13052022_Work-02.wav74 MB
- Tar_13052022_Czechia-02.wav177 MB
- Tar_13052022_Food-02.wav116 MB
- Tar_13052022_Work-01.wav74 MB
- Audio-Monologues
- Lat_30122020.wav7 MB
- Dam_06052022_3.wav5 MB
- Dam_01.wav27 MB
- Lat_2932021_5.wav19 MB
- Dam_06052022_2.wav15 MB
- Lat_26052021.wav77 MB
- Lat_2932021_4.wav16 MB
- Lat_2932021_3.wav6 MB
- Lat_2932021_2.wav15 MB
- Alep_27052021.wav7 MB
- Lat_2932021_1.wav37 MB
- Alep_23122020_4.wav19 MB
- Alep_23122020_3.wav35 MB
- Alep_09052021_2.wav3 MB
- Alep_23122020_2.wav23 MB
- Alep_09052021_1.wav9 MB
- Alep_23122020_1.wav16 MB