Showing posts with label commercial use of LDC data. Show all posts
Showing posts with label commercial use of LDC data. Show all posts

Monday, June 15, 2026

LDC June 2026 Newsletter

Maintaining LDC organization user accounts

LDC data and commercial technology development

New publications:

KAIROS Phase 1 Evaluation Source Data, Annotation, and Assessment

Multi-Language Conversational Telephone Speech 2014 – Spanish & Portuguese

LORELEI Multiway Translated Text

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Maintaining LDC organization user accounts
LDC encourages organization account administrators to review their LDC organization user accounts at least annually to remove users who are no longer affiliated with the organization. Users no longer affiliated with an organization cannot continue to access LDC data through the organization’s LDC account. As stated in LDC’s membership agreements and license agreements, LDC data cannot be shared outside the member/licensing organization. LDC reserves the right to deactivate user accounts if any suspicious activity is detected. Visit the User Accounts page for further information on user types and privileges.

LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

KAIROS Phase 1 Evaluation Source Data, Annotation, and Assessment was developed by LDC and contains the English and Spanish source data (text, video, images), manual annotations, reference knowledge graphs, the system output assessed during the evaluation, and human assessment results from the Phase 1 evaluation of the DARPA KAIROS Program. The Phase 1 evaluation focused on the improvised explosive bombing scenario with nine complex events and two surprise complex events in the mass shooting scenario.

Source data for each complex event consisted of 10-15 documents that included multimodal English and Spanish event-relevant and off-topic distractor documents. Manual annotation and assessment of event-relevant documents for 10 complex events are included in this release. Scenario-relevant events and relations were labeled for each document to develop a structured representation of temporally-ordered events, relations and arguments that expressed the scenario-relevant events in each complex event. A reference knowledge graph (Graph G) was developed for each event; systems were expected to match the Graph G with a given schema library. Assessment data includes human assessment judgments and the system output that was manually assessed for the end-to-end evaluation task.

The DARPA KAIROS (Knowledge-directed Artificial Intelligence Reasoning Over Schemas) program aimed to build technology capable of understanding and reasoning about complex real-world events in order to provide actionable insights to end users. KAIROS systems utilized formal event representations in the form of schema libraries that specified the steps, preconditions and constraints for an open set of complex events; schemas were then used in combination with event extraction to characterize and make predictions about real-world events in a large multilingual, multimedia corpus.

2026 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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Multi-Language Conversational Telephone Speech 2014 – Spanish & Portuguese was developed by LDC and is comprised of 123 hours of Spanish and Portuguese telephone speech. The data was collected to support research and technology evaluation in automatic language identification; portions of these recordings were used in the NIST 2015 and 2017 language recognition evaluations. The collection focused on language pair discrimination for 20 languages/dialects, some of which could be considered mutually intelligible or closely related. 

This corpus contains 569 recordings covering Brazilian Portuguese, Caribbean Spanish, European Spanish and Latin American Spanish. Participants were recruited by native speakers who contacted acquaintances in their social network. Those native speakers made one call, up to 8 minutes, to each acquaintance. Human auditors labeled the calls for language, quality, callee gender, dialect type and noise.

2026 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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LORELEI Multiway Translated Text consists of a fixed set of English texts (around 100,000 words) translated into 24 languages. It was developed by LDC for the DARPA LORELEI Program; the translations were included in the LORELEI representative language packs created by LDC in 2016-2019. 

The common word set was composed of English news documents (50%), LORELEI-domain English news documents (25%), and a phrasebook and elicitation corpus (25%). The phrasebook contained everyday colloquial phrases. The elicitation corpus was designed to represent linguistic structures. Texts were translated by a combination of professional translators and crowd-sourced translators. 

The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. Linguistic resources for LORELEI include Representative Language Packs and Incident Language Packs for over two dozen low resource languages, comprising data, annotations, basic natural language processing tools, lexicons and grammatical resources. Representative languages were selected to provide broad typological coverage, while incident languages were selected to evaluate system performance on a language whose identity was disclosed at the start of the evaluation.

2026 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Thursday, March 19, 2026

LDC March 2026 Newsletter

LDC data and commercial technology development 

New publications:

Ancient Chinese WordNet

CALLHOME Spanish Second Edition

CALLHOME Spanish Lexicon Second Edition

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LDC data and commercial technology development

For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

Ancient Chinese WordNet was developed by Nanjing Normal University and contains lexical and semantic information for Ancient Chinese vocabulary from the Pre-Qin period (before 221 BCE). The WordNet comprises 38,781 word forms and 55,100 senses, each manually linked to a corresponding synset in Princeton WordNet 1.6 and covering 22 noun categories, 15 verb categories, and additional adjective and adverb categories. The Ancient Chinese WordNet project began in 2012 with the goal of creating a structured lexical database to support linguistic research and natural language processing applications involving historical Chinese language materials.

2026 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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CALLHOME Spanish Second Edition was developed by LDC and contains 38 hours of speech from 120 unscripted telephone conversations between native Spanish speakers. This publication is a re-release of the original CALLHOME Spanish collection, combining CALLHOME Spanish Speech (LDC96S35) and CALLHOME Spanish Transcripts (LDC96T17), with additional transcription and updated directory structure, file formats, and documentation.

This corpus contains the 120 calls from CALLHOME Spanish Speech which represented training and development data and a subset of evaluation data. Participants spoke on topics of their choice in a single telephone call lasting up to 30 minutes. Calls were manually audited for language, recording quality, channel characteristics, dialect, and region. For this second edition, all audio was converted from SPHERE files to FLAC format, and the original training/development/test partitioning was removed. 

This release also features revised transcripts conforming to updated LDC transcription guidelines that addressed normalization of annotation formats, standardization of speaker-produced and background noises, application of foreign-language marking, whitespace cleanup, and corrections and consistency fixes.

The CALLHOME series consists of telephone conversations and transcripts developed by LDC and Rutgers, The State University of New Jersey, in support of research in speaker identification, language identification and related technologies. Languages in the series include American English, Egyptian Arabic, German, Japanese, Mandarin Chinese, and Spanish.

2026 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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CALLHOME Spanish Lexicon Second Edition was developed by LDC and contains 45,547 Spanish words with morphological, phonological, stress and frequency information. This second edition updates file formats, directory structure and documentation. The first edition is available as CALLHOME Spanish Lexicon (LDC96L16). The words in the lexicon were derived from 80 transcripts representing unscripted telephone conversations between native Spanish speakers contained in CALLHOME Spanish Second Edition LDC2026S04 and from various Spanish news texts.

The lexicon contains nine tab-separated information fields: (1) headword: orthographic form; (2) morph: morphological analysis of the headword; (3) pron: pronunciation of the headword; (4) stress: primary stress information of the word; (5) callh freq: frequency of the headword in CALLHOME transcripts; (6) madrid freq: frequency of the headword in Madrid Radio transcripts; (7) ap freq: frequency of the headword in Associated Press newswire; (8) reut freq: frequency of the headword in Reuters newswire; and (9) norte freq: frequency of the headword in El Norte newswire.

This release also includes a pronunciation dictionary derived from the lexicon in CMUdict format and the grapheme-to-phoneme (G2P) tools used to automatically generate pronunciations for the original lexicon.

2026 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee.

Monday, September 15, 2025

LDC September 2025 Newsletter

LDC data and commercial technology development

New publications:

Mixer 7 English Speech

AIDA Scenario 1 Evaluation Topic Source Data, Annotation and Assessment

LORELEI Hindi Representative Language Pack

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

Mixer 7 English Speech was developed by LDC and contains 12,321 hours of audio recordings of interviews, transcript readings and conversational telephone speech involving 222 distinct English speakers. This material was collected by LDC in 2010-2011 as part of the Mixer project, and the recordings were used in the 2012 NIST SRE test set.

Recruited speakers were connected through a robot operator to carry on casual conversations on a pre-set topic lasting up to 10 minutes. Participants also visited LDC’s human subjects collection lab equipped with a 14-microphone array where they participated in interviews and transcript readings and conducted telephone calls under varying conditions. Selected speaker metadata was also collected.  

2025 members can access this corpus through their LDC accounts. This corpus is a members-only release and is not available for non-member licensing. Contact ldc@ldc.upenn.edu for information about membership.

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AIDA Scenario 1 Evaluation Topic Source Data, Annotation and Assessment was developed by LDC and is comprised of English, Russian and Ukrainian web documents (text, video, image), annotations and assessments used in the AIDA Phase 1 pilot and final evaluations. The Phase 1 scenario focused on political relations between Russia and Ukraine in the 2010s. The material in this corpus covers the following events: Suspicious Deaths and Murders in Ukraine (January-April 2015); Odessa Tragedy (May 2, 2014); and Siege of Sloviansk and Battle of Kramatorsk (April-July 2014).

The corpus contains 10,522 documents, annotations for 386 of those documents, and assessment results covering 77,965 responses in 1,525 of those documents. Annotations were performed in three steps: (1) within-document labels for scenario-related entities, relations and events; (2) coreference annotation across documents by linking information elements to a knowledge base; and (3) indications of any relationship between labeled events/relations and hypotheses about the scenario. In the assessment phase, LDC annotators reviewed and judged system response files to provide evaluation organizers with a means for scoring submissions. Assessment tasks included zero-hop assessment, class-based assessment, graph assessment and hypothesis assessment. 

The DARPA AIDA (Active Interpretation of Disparate Alternatives) program aimed to develop a multi-hypothesis semantic engine to generate explicit alternative interpretations of events, situations and trends from a variety of unstructured sources. LDC supported AIDA by collecting, creating and annotating multimodal linguistic resources in multiple languages.

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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LORELEI Hindi Representative Language Pack contains over 26 million words of Hindi monolingual text, 363,00 words of which were translated into English, 1.07 million words of found Hindi-English parallel text, and 118,000 Hindi words translated from English data. Approximately 103,000 words were annotated for simple named entities and over 25,000 words were annotated for full entity (including nominals and pronouns), entity linking and situation frames (identifying entities, needs and issues). Data was collected from discussion forum, news, reference, social network, and weblogs.

The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations. Representative languages were selected to provide broad typological coverage.

The knowledge base for entity linking annotation is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Monday, June 16, 2025

LDC June 2025 Newsletter

LDC data and commercial technology development


New publications:

Chinese Sentence Pattern Structure Treebank
IWSLT 2022-2023 Shared Task Training, Development and Test Set
KAIROS Schema Learning Complex Event Annotation

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

Chinese Sentence Pattern Structure Treebank was developed at Beijing Normal University and Peking University. It contains 5,016 sentences and 119,627 tokens syntactically annotated following the concept of sentence constituent analysis which emphasizes sentence pattern structure. The source data consists of 27 chapters extracted from modern Mandarin and ancient Chinese works. There are three annotation layers: lexical sense and structural mode for dynamic words; syntactic structure for clauses; and inter-clause relation within complex sentence and sentence clusters. These structures can be visualized using the Jbw-viewer tool which is included in the release.

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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IWSLT 2022 - 2023 Shared Task Training, Development and Test Set was developed by LDC and contains 210 hours of Tunisian Arabic conversational telephone speech, transcripts, English translations, speaker metadata, and documentation. This material constitutes the training, development and test data used in the International Conference on Spoken Language Translation (IWSLT) Dialectal Speech Translation task (2022) and the Dialectal and Low-resource track (2023).

The telephone speech was collected by LDC in 2016-2017 from native speakers of Tunisian Arabic in Tunis. Speakers were recruited to make telephone calls to people in their social networks from a variety of noise conditions and handsets. Transcripts are orthographic following Buckwalter transliteration and cover 175 hours of the collected speech. IPA transcripts were added to a subset of the data. 

All transcribed segments were translated into English.

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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KAIROS Schema Learning Complex Event Annotation was developed by LDC to support the DARPA KAIROS program. It contains English and Spanish text, audio, video and image data labeled for 93 real-world complex events with event, relation and argument annotations linking to document provenance. Source data was collected from the web; 3431 root web pages were collected and processed, yielding 1919 text data files, 24019 image files, 1472 video files and 16 audio files.

The DARPA KAIROS (Knowledge-directed Artificial Intelligence Reasoning Over Schemas) program aimed to build technology capable of understanding and reasoning about complex real-world events in order to provide actionable insights to end users. KAIROS systems utilized formal event representations in the form of schema libraries that specified the steps, preconditions and constraints for an open set of complex events; schemas were then used in combination with event extraction to characterize and make predictions about real-world events in a large multilingual, multimedia corpus.

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.


Monday, March 17, 2025

LDC March 2025 Newsletter

LDC data and commercial technology development

New publications:

2015 NIST Language Recognition Evaluation Test Set

The Xi’an Multi-Language Learner Corpus

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

2015 NIST Language Recognition Evaluation Test Set was developed by LDC and NIST. It contains the evaluation test set for the 2015 NIST Language Recognition Evaluation (LRE), approximately 867 hours of conversational telephone speech (CTS) and broadcast narrowband speech (BNBS) collected by LDC in 20 languages over 6 clusters of related languages: Arabic (Egyptian, Iraqi, Levantine, Maghrebi, Modern Standard Arabic); Spanish (Caribbean, European, Latin American, Brazilian Portuguese); English (British, Indian, General American English); Chinese (Cantonese, Mandarin, Min Nan, Wu); Slavic (Polish, Russian); and French (West African, Haitian Creole).

The CTS data includes calls between individuals in the same social networks lasting 8-15 minutes and telephone speech from the IARPA Babel series collected in 2012-2013 from speakers using a range of phone types in diverse settings with varying noise conditions. The BNBS data was collected by LDC from streaming and satellite radio programming, focusing on programs that included narrowband speech (e.g., call-ins to a talk show).

The goal of NIST's LRE evaluations is to establish the baseline of current performance capability for CTS language recognition and to lay the groundwork for further research efforts. LRE15 expanded the range of test segment durations and added a test condition that allowed systems to make use of unrestricted training data when developing models

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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The Xi’an Multi-Language Learner Corpus was developed by Xi'an International Studies University (XISU) and is comprised of 526 argumentative essays in 15 languages by Chinese L1 university students studying second languages, along with student metadata and writing prompts. It was developed to support second language learner research and to provide a database for cross-linguistic comparison of second languages. 

Data was collected in 2023 and 2024 from students at XISU and Yunnan Minzu University (YMU) who were linguistic majors or studying one of the foreign languages available at XISU and YMU. Off-topic essays and incomplete texts were excluded.

2025 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Monday, September 16, 2024

LDC September 2024 Newsletter

LDC data and commercial technology development


New publications:

L2-KSU Native and Non-Native Arabic Speech

MATERIAL Somali-English Language Pack

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications: 

L2-KSU Native and Non-Native Arabic Speech was developed by King Saud University (KSU) and contains approximately six hours of Modern Standard Arabic read speech from 80 subjects, along with transcripts and speaker metadata.

The speech data was collected in 2022 from 40 native and 40 non-native speakers. Native speakers were from Saudi Arabia, Egypt, and Palestine and provided audio recordings through the crowd sourcing platform Khamsat. Non-native speakers were Central and West African students enrolled in KSU's Arabic Linguistics Institute; they provided speech recordings on site. All subjects read a series of ten sentences, repeating each sentence multiple times.

2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee.

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MATERIAL Somali-English Language Pack was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) MATERIAL (Machine Translation for English Retrieval of Information in Any Language) program. It contains 80 hours of Somali conversational telephone speech, transcripts, English translations, annotations and queries.

Calls were made using different telephones (e.g., mobile, landline) from a variety of environments. Transcripts cover approximately 10% of the speech files, and approximately 4% of the speech files were translated into English. This release also includes domain annotations, English queries and their relevance annotations. 

The MATERIAL program focused on underserved languages with the ultimate goal to build cross language information retrieval systems to find speech and text content using English search queries.

2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee.


Monday, June 17, 2024

LDC June 2024 Newsletter

LDC data and commercial technology development

New publications:

Diaspora Tibetan Speech

AIDA Scenario 2 Practice Topic Annotation

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:
 
Diaspora Tibetan Speech was developed at Yale University. It contains 28 hours of Tibetan elicited speech by 73 speakers from the diaspora Tibetan community in Kathmandu, Nepal, along with transcripts, elicitation materials and speaker metadata.

Recordings were collected in 2016. All speakers were adults and varied in age as well as age of diaspora. A substantial number of speakers were born in Nepal. Each speaker contributed one recording comprising a series of elicitation tasks: some demographic information; a word list and numbers; some sentences in isolation; a scripted story; and free speech based on "frog story" type illustrations.  Annotation and metadata formats include PDF and Word (some transcripts), Excel (some transcripts, speaker metadata) and Praat TextGrids (word and number lists). 

2024 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. 

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AIDA Scenario 2 Practice Topic Annotation was developed by LDC and is comprised of annotations for 29 English, Russian and Spanish documents (text, image and video) from AIDA Scenario 2  Practice Topic Source Data (LDC2024T04), specifically, the set of practice documents designated for annotation in Phase 2.

Annotations are presented as tab separated files in the following categories for each topic:

  • Mentions: single references in source data to a real-world entity or filler, event, or relation. 
  • Slots: pre-defined roles in an event or relation filled by an argument (entity mention).
  • Linking: entity mentions linked to entries in the knowledge base as a method of indicating the real-world entity to which an entity referred.

2024 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

 

 

Sunday, March 17, 2024

LDC March 2024 Newsletter

LDC data and commercial technology development 

New publications:

RATS Low Speech Density

BabyEars Affective Vocalizations

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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:
RATS Low Speech Density was developed by LDC and is comprised of 87 hours of English, Levantine Arabic, Farsi, Pashto and Urdu speech and non-speech samples. The recordings were assembled by concatenating a randomized selection of speech, communications systems sounds, and silence. This corpus was created to measure false alarm performance in RATS speech activity detection systems.
 
The source audio was extracted from RATS development and progress sets and consists of conversational telephone speech recordings collected by LDC. Non-speech samples were selected from communications systems sounds, including telephone network special information tones, radio selective calling signals, HF/VHF/UHF digital mode radio traffic, radio network control channel signals, two-way radio traffic containing roger beeps, and short duration shift-key modulated handset data transmissions.
 
The goal of the RATS (Robust Automatic Transcription of Speech) program was to develop human language technology systems capable of performing speech detection, language identification, speaker identification and keyword spotting on the severely degraded audio signals that are typical of various radio communication channels, especially those employing various types of handheld portable transceiver systems.

2024 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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BabyEars Affective Vocalizations contains 22 minutes of spontaneous English speech by 12 adults interacting with their infant children, for a total of 509 infant-directed utterances and 185 adult-directed or neutral utterances. Speech data was collected in a quiet room during a one-hour session where each parent was asked to play and otherwise interact normally with their infant (aged 10-18 months). A trained research assistant then extracted discrete utterances and classified them in three categories: approval, attention and prohibition.

2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee.

Friday, September 15, 2023

LDC September 2023 Newsletter

LDC data and commercial technology development 

New publications:

CALLFRIEND Russian Speech

CALLFRIEND Russian Text
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LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

CALLFRIEND Russian Speech was developed by LDC and consists of 48 hours of telephone conversations (100 recordings) between native speakers of Russian. The calls were recorded in 1999 as part of the CALLFRIEND collection, a project designed primarily to support research in automatic language identification. One hundred native Russian speakers living in the continental United States each made a single phone call, lasting up to 30 minutes, to a family member or friend living in the United States.

All recordings involved domestic calls routed through LDC’s automated telephone collection platform and stored as 2-channel (4-wire) 8-KHz mu-law samples taken directly from a public telephone network via a T-1 circuit. Each audio file is a FLAC-compressed MS-WAV (RIFF) format audio file containing 2-channel, 8-KHz, 16-bit PCM sample data.

This release includes call metadata, including speaker gender, the number of speakers on each channel and call duration.

Corresponding transcripts and a lexicon are available in CALLFRIEND Russian Text (LDC2023T09).

2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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CALLFRIEND Russian Text contains the corresponding transcripts and a lexicon for CALLFRIEND Russian Speech, that is, 48 hours of telephone conversations (100 recordings) between native Russian speakers. 

The transcripts have four main fields on each line (begin_offset, end_offset, speaker_label, transcript_text) separated by tabs. Each contains a list of time-stamped segments in order according to their begin_offset values, with no blank lines.

The lexicon covers the word forms in the 97 transcript files. The main lexicon table contains three columns per row: Cyrillic orthography, phonetic transliteration and numeric representation of syllabic stress.

Corresponding speech data is available as CALLFRIEND Russian Speech (LDC2023S08).

2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Thursday, June 15, 2023

LDC June 2023 Newsletter

LDC at ACL 2023

LDC data and commercial technology development

New publications:

Moroccan Arabic – English Lexical Database

LORELEI Indonesian Representative Language Pack

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LDC at ACL 2023

LDC will be exhibiting at ACL 2023, held this year July 9-14 in Toronto, Canada. Stop by our booth to learn more about recent developments at the Consortium and the latest publications. LDC will post conference updates via Twitter and Facebook. We look forward to seeing you there!

LDC data and commercial technology development

For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications:

Moroccan Arabic - English Lexical Database was developed by LDC. It contains a set of five interrelated tables presenting each Moroccan Arabic word as an orthographic form in Arabic script and a pronunciation form in International Phonetic Alphabet (IPA) format. This release contains over 21,000 Moroccan Arabic words in Arabic script and IPA notation and more than 33,000 English tokens.

This lexical database is the result of a collaboration with Georgetown University Press (GUP) to enhance and update three dialectal Arabic dictionaries -- Iraqi, Moroccan and Syrian -- originally published in paper form in the 1960s by GUP.  LDC also undertook to develop a lexical database for each dialect. The Georgetown Dictionary of Moroccan Arabic was published in 2019; this work was based on, and expanded, A Dictionary of Moroccan Arabic.

The several enhancements developed by LDC included facilitating comparisons across Arabic dialects and Modern Standard Arabic by providing Arabic script spellings and IPA pronunciations to Moroccan words and phrases; promoting ease of use by language learners and researchers by developing reasonable orthographic conventions for applying the Arabic alphabet to the dialect; and facilitating a user's understanding of morphological and lexical relations by adding information on the linguistic structures of Moroccan Arabic.

2023 members can access this corpus through their LDC accounts provided they have submitted a signed copy of the special license agreement. Non-members may license this data for a fee.

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LORELEI Indonesian Representative Language Pack is comprised of over 17 million words of Indonesian monolingual text, 950,000 million words of found Indonesian-English parallel text, and 92,000 Indonesian words translated from English data. Over 113,000 words were annotated for named entities and more than 24,000 words were annotated for entity discovery and linking and situation frames (identifying entities, needs and issues). Data was collected from discussion forum, news, reference, social network, and weblogs.

The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations. Representative languages were selected to provide broad typological coverage.

The knowledge base for entity linking annotation is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Wednesday, March 15, 2023

LDC March 2023 Newsletter

LDC’s 30th anniversary year ends 

LDC data and commercial technology development


New publications:

Mixer 3 Speech

LORELEI Tamil Representative Language Pack

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LDC’s 30th anniversary year ends   

We hope you enjoyed the monthly data spotlights in celebration of LDC’s 30th anniversary year, April 2022-March 2023. We would not have achieved this milestone without the continued support and collaboration of our members, friends, and the community. We are grateful. As we enter our fourth decade, we pledge to continue to serve the community and our members by distributing high quality, diverse data and by providing top-notch member services and research program support. 

LDC data and commercial technology development

For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

New publications: 

Mixer 3 Speech contains 3,200 hours of conversational telephone speech involving 3,875 speakers, 19,595 telephone recordings and 26 distinct languages. This material was collected by LDC from 2005-2007 as part of the Mixer project, and recordings in this corpus were used in NIST Speaker Recognition Evaluation and NIST Language Recognition Evaluation corpora, including 2006 SRE and 2007 LRE.

Recordings were generated using LDC's computer telephony system. Recruited speakers were connected through a robot operator to carry on casual conversations lasting up to 10 minutes. Subjects fluent in languages other than English were asked to complete at least one non-English call. Metadata includes the number of calls per subject and language as well as speaker demographic information.

2023 members can access this corpus through their LDC accounts. This corpus is a members-only release and is not available for non-member licensing. Contact ldc@ldc.upenn.edu for information about membership.

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LORELEI Tamil Representative Language Pack is comprised of over 41 million words of Tamil monolingual text, 680,000 words of found Tamil-English parallel text, and 226,000 Tamil words translated from English data. Approximately 78,000 words were annotated for named entities and over 24,000 words were annotated for entity discovery and linking and situation frames (identifying entities, needs and issues). Data was collected from discussion forum, news, reference, social network, and weblogs.

The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations. Representative languages were selected to provide broad typological coverage.

The knowledge base for entity linking annotation is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

2023 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

Monday, October 17, 2022

LDC October 2022 Newsletter

Membership Year 2023 publication preview 

LDC data and commercial technology development 

30th Anniversary Highlight: ACE 

New publications:
Rime-Cantonese: A Normalized Cantonese Jyutping Lexicon
2017 NIST Language Recognition Evaluation Training and Development Sets
LORELEI Bengali Representative Language Pack


Membership Year 2023 publication preview The 2023 membership year is approaching and plans for next year’s publications are in progress. Among the expected releases are: 

  • AIDA Ukrainian Broadcast and Telephone Speech Audio and Transcripts: 156 hours of Ukrainian conversational telephone speech and broadcast news with 1.2 million words of corresponding orthographic transcripts 
  • 2019 NIST SRE: audiovisual and leaderboard challenge sets based on amateur videos and Tunisian Arabic telephone speech, respectively   
  • DEFT English ERE: English text from assorted genres annotated for entities, relations, and events  
  • Mixer 3 and Mixer 7 speech collections: thousands of hours of telephone speech and metadata from Mixer 3 (multiple languages) and Mixer 7 (Spanish, plus interviews and transcript readings)  
  • CALLFRIEND Russian: 100 telephone conversations among native speakers, transcripts, and a lexicon, released in separate speech and text data sets 
  • REMIX Telephone Collection: English telephone speech from 385 participants in previous Mixer studies 
  • LORELEI: representative and incident language packs containing monolingual text, bi-text, translations, annotations, supplemental resources, and related tools in various languages (e.g., Indonesian, Swahili, Tagalog, Tamil, Zulu) 


Check your inbox in the coming weeks for more information about membership renewal.  

LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing page for further information.

30th Anniversary Highlight: ACE 
The objective of the Automatic Content Extraction (ACE) program was to develop the capability to extract meaning (entities, relations and events) from multimedia sources (Doddington, et al., 2004). LDC supported ACE by creating annotation guidelines, corpora and other linguistic resources, including training and test data for the common task research evaluations (Strassel, et al., 2003Huang, et al., 2004).
There are multiple data sets in LDC’s Catalog from the program. One that regularly makes the list of LDC’s top ten most licensed corpora is ACE 2005 Multilingual Training Corpus (LDC2006T06). This data set contains 1,800 files of mixed genre text in English, Arabic, and Chinese annotated for entities, relations, and events. The genres include newswire, broadcast news, broadcast conversation, weblog, discussion forums, and conversational telephone speech. 
Another popular data set, ACE 2004 Multilingual Training Corpus (LDC2005T09), consists of varied genre text in English (158,000 words), Chinese (307,000 characters, 154,000 words), and Arabic (151,000 words) annotated for entities and relations.
ACE 2007 Multilingual Training Corpus (LDC2014T18) has the complete set of Arabic and Spanish training data for the 2007 ACE technology evaluation, specifically, Arabic and Spanish newswire data and Arabic weblogs annotated for entities and temporal expressions.
Other ACE corpora in the Catalog include ACE 2005 SpatialML Annotations in English and Mandarin (LDC2008T03LDC2010T09, LDC2011T02), Datasets for Generic Relation Extraction (reACE)TIDES Extraction (ACE) 2003 Multilingual Training DataACE-2 Version 1.0ACE Time Normalization (TERN) 2004 English Training Data v 1.0 (TERN), and more. 

For the full list of available ACE data, visit LDC’s Catalog and select the ACE research project in the search menu. For more information about linguistic resources for the ACE Program, including annotation guidelines, task definitions and other documentation, visit LDC's ACE webpage.


New publications:Rime-Cantonese: A Normalized Cantonese Jyutping Lexicon was developed by the Cantonese Computational Linguistics Infrastructure Working Group. It contains approximately 130,000 Cantonese character, word, and phrase entries paired with their corresponding romanized pronunciations in Jyutping, a scheme created by The Linguistic Society of Hong Kong.Data was collected from a variety of physical and online sources. The character collection was subjected to a normalization process for differences between traditional and simplified Chinese, regional differences and other variants in Chinese characters, and differences in orthography.2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.


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2017 NIST Language Recognition Evaluation Training and Development Sets contains training and development material for the 2017 NIST Language Recognition Evaluation. It consists of 2,100 hours of conversational telephone speech, broadcast conversation, broadcast narrow band speech, and speech from video in the following 14 languages, dialects, and varieties: Arabic (Iraqi, Levantine, Maghrebi, Egyptian), English (British, American), Polish, Russian, Portuguese (Brazilian), Spanish (Caribbean, European, Latin American Continental), and Chinese (Mandarin, Min Nan). The 2017 evaluation focused on differentiating closely related language pairs. Source data is from LDC's CALLFRIEND and Fisher telephone collections, the VAST video collection, various broadcast sources, and earlier NIST LRE test sets.
 
2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.

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LORELEI Bengali Representative Language Pack was developed by LDC and is comprised of approximately 144 million words of Bengali monolingual text, 96,000 Bengali words translated from English data, and over 2 million words of found Bengali-English parallel text. Approximately 86,000 words were annotated for named entities and up to 25,000 words were annotated for entity discovery and linking and situation frames (identifying entities, needs and issues). Data was collected from news, social network, and weblogs.The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations. Representative languages were selected to provide broad typological coverage.The knowledge base for entity linking annotation is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.