Audio (529)
Text (413)
Video (19)
Available (896)
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Parallel (20)
Other (1)
TEI (9)
Tourism (3)
Science (1)

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896 Language Resources (Page 1 of 45)

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 Accented English GlobalPhone    
  • English

ID: ELRA-S0389

ISLRN: 574-579-221-841-3

The Accented English part of the GlobalPhone resources contains 63 recording sessions of Bulgarian, Chinese, German, and Indian native speakers reading 37 English sentences each, produced in GlobalPhone-style, i.e. 16kHz PCM encoded audio recordings of utterance-segmented read speech from the new...

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 ACCOR - English    
  • English

ID: ELRA-S0001

ISLRN: 936-783-643-804-4

ACCOR is a unique acoustic and articulatory database recorded as part of the ESPRIT- ACCOR project investigating cross-language acoustic-articulatory correlations in coarticulatory processes. The European Languages covered are: Catalan, English, French, German, Irish Gaelic, Italian and Swedish. ...

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 ACL RD-TEC: A Reference Dataset for Terminology Extraction and Classification Research in Computational Linguistics    
  • English

ID: ELRA-T0375

ISLRN: 699-305-362-089-6

Automatic Term Recognition (ATR) is a research task that deals with the identification of domain-specific terms. Terms, in simple words, are textual realization of significant concepts in an expertise domain. Additionally, domain-specific terms may be classified into a number of categories, in wh...

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 Acoustic database for Polish concatenative speech synthesis    
  • Polish

ID: ELRA-S0342

ISLRN: 305-222-372-690-4

This database consists of 1443 nonsense words including all the diphones for the Polish language. The diphone is always placed at an unstressed syllable. The neighbourhood doesn’t influence the co-articulation of the diphone. The database includes information such as: the name of the diphone, co...

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 Acoustic database for Polish unit selection speech synthesis    
  • Polish

ID: ELRA-S0339

ISLRN: 981-910-282-065-4

This database contains parliamentary statements and newspaper reviews read by a semi-professional male speaker. It consists of a selection of 2150 sentences annotated and manually verified, including 100 rare phonemes in words. Prompts vary in length from 2.3 to 13.4 seconds, with an average leng...

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 aGender    
  • German

ID: ELRA-S0365

ISLRN: 038-476-412-610-4

aGender contains speech sample recordings over public telephone lines with read and (semi-)spontaneous speech. Native German speakers called a voice portal from their private phone, and read text + answered some open questions. The purpose of the corpus is the automatic detection of gender and/or...

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 Albayzin corpus    
  • Spanish; Castilian

ID: ELRA-S0089

ISLRN: 443-392-902-600-9

This corpus consists of 3 sub-corpora of 16 kHz 16 bits signals, recorded by 304 Castillian speakers. The 3 sub-corpora are: - Phonetic corpus: 6,800 utterances of phonetically balanced sentences, including 1000 with phonetic segmentation. - Geographic corpus: 6,800 utterances of sentences ext...

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 Alcohol Language Corpus (BAS ALC)    
  • German

ID: ELRA-S0299

ISLRN: 780-368-852-139-3

ALC contains recordings of German speakers that are either intoxicated or sober. The type of speech ranges from read single digits to full conversation style. Recordings were done during drinking test where speakers drank beer or wine to reach a self-chosen level of alcoholic intoxication. The ac...

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 Al-Hayat Arabic Corpus    
  • Arabic

ID: ELRA-W0030

ISLRN: 365-777-769-398-7

The corpus was developed in the course of a research project at the University of Essex, in collaboration with the Open University. The corpus contains Al-Hayat newspaper articles with value added for Language Engineering and Information Retrieval applications development purposes. The data have ...

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 ALLIES Corpus    
  • French

ID: ELRA-S0486

ISLRN: 397-116-696-859-2

The ALLIES Corpus was produced within the European CHIST-Era project ALLIES. The ALLIES project enabled to carry out a campaign for the evaluation of Broadcast News across time diarization systems using French data. This project is an extension of the previous ESTER, REPERE and ETAPE evaluation c...

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 American/Canadian English Speech Recognition Corpus (headset+mobile)    
  • English

ID: ELRA-S0228-102

ISLRN: 992-319-311-431-0

This corpus comprises 12,974 entries uttered by 30 speakers (15 males and 15 females), recorded over 2 channels (headset and mobile in noisy restaurant/shopping mall/info center/hospital/station/car). Speech samples are stored as a sequence of 16-bit 48kHz for a total of 12 hours of speech per ch...

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 American English Conversational Speech Recognition Corpus (Multi-Channel)    
  • English

ID: ELRA-S0228-93

ISLRN: 576-996-121-023-5

This corpus was recorded by 20 speakers (10 males and 10 females), over 7 channels (multi-channel in quiet office/home). Speech samples are stored as a sequence of 16-bit 16 kHz for a total of 10 hours of speech per channel.

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 American English Speech Recognition Corpus (Desktop)    
  • English

ID: ELRA-S0228-113

ISLRN: 703-568-790-770-5

This corpus was recorded in both quiet and noisy environments over 2 channels and collected from a total of 50 speakers, including 24 males and 26 females, all of whom have been carefully screened to ensure their standard and clear pronunciation. The audio scripts cover information such as text m...

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 American English Speech Recognition Corpus (Desktop)    
  • English

ID: ELRA-S0228-79

ISLRN: 254-019-000-249-3

This corpus comprises 49,990 entries uttered by 50 speakers (25 males and 25 females), recorded over 2 channels (desktop in quiet office). Speech samples are stored as a sequence of 16-bit 16kHz for a total of 24.9 hours of speech per channel.

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 American English Speech Recognition Corpus (Mobile) - 14.67 hours    
  • English

ID: ELRA-S0228-73

ISLRN: 817-988-141-738-4

This corpus comprises 14,988 entries uttered by 50 speakers (23 males and 27 females), recorded over the mobile telephone network. Speech samples are stored as a sequence of 16-bit 16 kHz for a total of 14.67 hours of speech.

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 American English Wake-up Words Speech Recognition Corpus (Mobile)    
  • English

ID: ELRA-S0228-58

ISLRN: 968-856-860-742-9

The corpus contains the recordings of 38,718 utterances of American English mobile Keywords speech data which were from 149 speakers(72 males and 77 females). Each speaker was designed to record 1 session, totally 260 utterances in quiet or noisy environments. The total pure recording time is abo...

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 American Spanish Recognition Corpus (Desktop+Mobile)    
  • English

ID: ELRA-S0228-68

ISLRN: 100-009-143-020-4

This corpus comprises 33,527 entries uttered by 40 speakers (21 males and 19 females), recorded over 2 channels (desktop in quiet office and mobile in noisy restaurant). Speech samples are stored as a sequence of 16-bit 16kHz for a total of 14.7 hours of speech per channel.

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 Amharic-English bilingual corpus    
  • Amharic
  • English

ID: ELRA-W0074

ISLRN: 590-255-335-719-0

The Amharic-English bilingual corpus contains parallel text from legal and news domains in Amharic script, in transliterated form and in English. The size of the corpus is of 232,653 words in Amharic and 291,701 in English. This parallel corpus contains documents from two domains, namely legal...

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 ANITA (Audio eNhancement In Telecom Applications)    
  • English
  • French
  • German
  • Spanish; Castilian

ID: ELRA-S0156

ISLRN: 537-894-870-719-4

ANITA (Audio eNhancement In secured Telecommunication Applications) is a European project launched on the initiative of EADS TELECOM with the objective of reducing audio acoustics noise in secured communications in adverse environments (sirens, alarms, engines, water pumps, stress situations, etc...

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 Annotated tweet corpus in Arabizi, French and English    
  • Arabic
  • English
  • French

ID: ELRA-W0323

ISLRN: 482-848-308-105-6

The annotated tweet corpus in Arabizi, French and English was built by ELDA on behalf of INSA Rouen Normandie (Normandie Université, LITIS team), in the framework of the SAPhIRS project (System for the Analysis of Information Propagation in Social Networks), funded by the DGE (Direction Générale ...

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