Showing posts with label KAIROS. Show all posts
Showing posts with label KAIROS. 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.

Monday, February 16, 2026

LDC February 2026 Newsletter

LDC membership discounts expire March 2 

Spring 2026 data scholarship recipient 


New publications:

2022 NIST Language Recognition Evaluation Test and Development Sets

KAIROS Schema Learning Background Source Data

LORELEI Russian Representative Language Pack

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LDC membership discounts expire March 2 
Time is running out to save on 2026 membership fees. Renew your LDC membership, rejoin the Consortium, or become a new member by March 2 to receive a 10% discount. For more information on membership benefits and options, visit Join LDC.


Spring 2026 data scholarship recipient 

Congratulations to the recipient of LDC’s Spring 2026 data scholarship:

Doma Akshitha Reddy: Chaitanya Bharathi Institute of Technology (India): Bachelor of Engineering, Information Technology. Doma is awarded copies of TIMIT Acoustic-Phonetic Continuous Speech Corpus and The CMU Kids Corpus for their work in child speech. 

Since 2010, LDC has awarded scholarships to successful student applicants twice each year. To date more than 242 corpora have been distributed to 162 students across 38 countries. We proudly celebrate their achievements and the contributions their research has made to the broader community. 

The next round of applications will be accepted in September 2026. For information about the program, visit the Data Scholarships page.


New publications:

2022 NIST Language Recognition Evaluation Test and Development Sets was developed by LDC and  NIST and contains the test and development data, metadata, answer keys, and documentation for the 2022 NIST Language Recognition Evaluation (LRE22). The source data is comprised of 222 hours of conversational telephone speech (CTS) and broadcast narrowband speech (BNBS) in 14 languages: Afrikaans, Tunisian Arabic, Algerian Arabic, Libyan Arabic, South African English, Indian-accented South African English, North African French, Ndebele, Oromo, Tigrinya, Tsonga, Venda, Xhosa and Zulu.

For the CTS collections, a small number of native speakers made single calls to multiple individuals in their social network. Calls lasted 8-15 minutes; speakers were free to discuss any topic. The BNBS data was collected from streaming radio programming, focused on broadcasts that included narrowband speech (e.g., call-ins to a talk show). Portions of the CTS callee call sides and portions of each broadcast recording were manually audited by native speakers to verify language and quality.

LRE22 emphasized language recognition for African languages, including low resource languages, and expanded the range of test segment durations. Further information about the 2022 evaluation can be found in the 2022 NIST Language Recognition Evaluation Plan. 

2026 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 Background Source Data was developed by LDC and includes 14,000 English and Spanish documents representing text, audio, video, image, and multimedia resources collected during the DARPA KAIROS program as supplemental background source data for the KAIROS Schema Learning Corpus (SLC). The purpose of the supplemental collection was to increase the amount of English and Spanish data with multimedia components for schema learning and to add domains not well represented in existing Spanish data. The supplemental data in this release includes material from the business and logistics domains, instructional documents and multimedia news.

The complete set of SLC background source data (including the data in this publication) totaled 16.2 million English, Russian and Spanish documents and more than 125,000 audio, video, image, or multimedia resources. A large portion of that data was drawn from pre-existing LDC datasets.

The SLC and KAIROS Schema Learning Complex Event Annotation (LDC2025T07), containing English and Spanish text, audio, video, and image material labeled for 93 real-world complex events, constitute the data used by KAIROS system developers for schema learning.

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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LORELEI Russian Representative Language Pack contains over 1.26 billion words of Russian monolingual text, 360,00 words of which were translated into English, 3 million words of found Russian-English parallel text, and 87,000 Russian words translated from English data. Approximately 83,000 words were annotated for simple named entities, around 26,000 words were annotated for full entity (including nominals and pronouns), entity linking and situation frames (identifying entities, needs and issues) and nearly 9,000 words were covered by noun phrase chunking annotation. 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).

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

Wednesday, October 15, 2025

LDC October 2025 Newsletter

Membership year 2026 publication preview 

Fall 2025 data scholarship recipients 

New publications:

KAIROS Phase 2 Quizlet

BOLT CTS CALLFRIEND CALLHOME Egyptian Arabic Audio

BOLT CTS CALLFRIEND CALLHOME Egyptian Arabic Transcripts and Translations

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Membership year 2026 publication preview 

The 2026 membership year is approaching and plans for next year’s publications are in progress. Among the expected releases are:  

  • KAIROS schema learning corpus background data and Phase 1 evaluation datasets: multimodal English and Spanish source data and annotations for reasoning about complex real-world events 
  • CALL MY NET 2: 800+ hours of Tunisian-Arabic conversational telephone speech from over 400 speakers to support text independent speaker recognition, used in the 2018 NIST Speaker Recognition Evaluation
  • Multi-language conversational telephone speech: multiple releases, hundreds of hours of speech from speakers of confusable linguistic varieties (Arabic, Chinese, English, French, Slavic, Spanish) to support language identification
  • CALLHOME Omnibus releases: combined speech and transcript datasets with updated directory structure, file formats and documentation, and lexicons (Chinese, English, German, Japanese, Spanish)
  • IARPA MATERIAL language packs: conversational telephone speech, transcripts, English translations, annotations and queries in multiple languages (e.g., Lithuanian, Pashto, Swahili, Tagalog)

Check your inbox for more information about membership renewal.

Fall 2025 data scholarship recipients

Congratulations to the recipients of LDC's Fall 2025 data scholarships:

Lasidu Dilshan: University of Moratuwa (Sri Lanka): BSc, Electronic and Telecommunication Engineering. Lasidu is awarded a copy of Asian Elephant Vocalizations LDC2010S05 for his work in elephant voice enhancement and classification.

Máté Gedeon: Budapest University of Technology and Economics (Hungary): PhD candidate, Department of Telecommunications and Artificial Intelligence. Máté is awarded a copy of Switchboard-1 Release 2 LDC97S62 for his work in simulated conversation generation.

Ping He: Northeastern University (USA): Student, Khoury College of Computer Sciences. Ping is awarded a copy of ETS Corpus of Non-Native Written English LDC2014T06 for their work in native language identification.

Thiyazen Iskander: Maulana Azad College of Arts, Science & Commerce (India), affiliated with Babasaheb Ambedkar Technological University (India): PhD candidate, Linguistics, Department of English. Thiyazen is awarded copies of Arabic Morphological Analyzer (SAMA) Version 3.1 LDC2010L01 and Arabic Treebank Part 1 v. 4.1 LDC2010T13 for his work in morphosyntactic analysis of short passives in Standard Arabic.

Michael Mooney: University of Glasgow (United Kingdom): PhD candidate, School of Computing Sciences. Michael is awarded copies of Treebank-2 LDC95T7 and BLLIP 1987-89 WSJ Corpus Release LDC2000T43 for their work in eye-tracking for text-centered modeling.

Abraham Sanders: Rensselaer Polytechnic Institute (USA): PhD candidate, Cognitive Science. Abraham is awarded a copy of Switchboard-1 Release 2 LDC97S62 for his work in spoken dialogue systems.


New publications:

KAIROS Phase 2 Quizlet was developed by LDC and contains English and Spanish text, video and image data and annotations used for pre-evaluation research and system development during Phase 2 of the DARPA KAIROS program. KAIROS Quizlets were a series of narrowly defined tasks designed to explore specific evaluation objectives enabling KAIROS system developers to exercise individual system components on a small data set prior to the full program evaluation. This corpus contains the complete set of Quizlet data used in Phase 2 which focused on five real-world complex events within the Disease Outbreak scenario. 

Source data was collected from the web; 66 root web pages were collected and processed, yielding 65 text data files, 890 image files and 10 video files. Annotation steps included labeling scenario-relevant events and relations for each document to develop a structured representation of temporally ordered events, relations and arguments; generating a reference knowledge graph; and linking labeled entries to a knowledge base derived from a Wikidata-based ontology.

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.


BOLT CTS CALLFRIEND CALLHOME Egyptian Arabic Audio was developed by LDC and consists of 116 hours of speech from 274 unscripted telephone conversations between native speakers of the Arabic dialect spoken in Egypt. The calls were collected by LDC in the CALLFRIEND and CALLHOME series where participants called family members or close friends and spoke on topics of their choice. Around 33% of the recordings (92 calls) are publicly released for the first time. The remaining 182 recordings were previously published by LDC in various CALLFRIEND, CALLHOME and HUB5 Arabic datasets. 

The DARPA BOLT (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, conversational telephone speech, text messaging and chat -- in Chinese, Egyptian Arabic and English. The material in this release represents the unannotated Egyptian Arabic source conversational telephone speech. The telephone data was transcribed, translated, and annotated for various tasks in the BOLT program including word alignment, treebanking, and co-reference.

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

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BOLT CTS CALLFRIEND CALLHOME Egyptian Arabic Transcripts and Translations contains transcripts and corresponding English translations for the conversational telephone speech in BOLT CTS CALLFRIEND CALLHOME Egyptian Arabic Audio and was developed by LDC to support the DARPA BOLT program. 

Transcribers were required to produce a verbatim transcript of all speech within a file using the CODA orthographic approach; diacritics were not included. Some transcripts contain redactions for potential personally identifying information. All speech data was transcribed and is divided into training, development, and evaluation partitions.

The goal of the BOLT translation task was to translate the Arabic transcripts into fluent English while preserving the meaning present in the original Arabic text. Transcripts in the development and evaluation partitions received first pass and gold standard translations. 99% of the transcripts were translated into English.

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

Friday, August 15, 2025

LDC August 2025 Newsletter

LDC at Interspeech 2025

Fall 2025 LDC data scholarship program 


New publications:

Mixer 6 – ChiME 8 Transcribed Calls and Interviews 

Abstract Meaning Representation 2.0 – Machine Translations 

KAIROS Phase 1 Quizlet 

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LDC at Interspeech 2025
LDC will be exhibiting at Interspeech 2025, held this year August 17-21 in Rotterdam, the Netherlands. Stop by our booth to say hello and learn about the latest developments at the Consortium. Also be on the lookout for the following presentations, posters and special sessions featuring LDC work: 

Comparative Evaluation of Acoustic Feature Extraction Tools for Clinical Speech Analysis
Monday, August 18, 11:00-13:00 - Area5-Oral1 - Speech Analysis, Detection and Classification 1

Reasoning-Based Approach with Chain-of-Thought for Alzheimer’s Detection Using Speech and Large Language Models
Tuesday, August 19, 13:30-15:30 - Area1-Poster2B - Databases and Progress in Methodology

Special Session: Challenges in Speech Collection, Curation and Annotation
Wednesday, August 20, 13:30-15:30 - Area14-SS7 – Part 1
Wednesday, August 20, 16:00-18:00 - Area14-SS8 – Part 2

TELVID: A Multilingual Multi-modal Corpus for Speaker Recognition
Thursday, August 21, 13:30-15:30 - AREA4-Oral8 – Speaker Recognition 

LDC also supported the Interspeech 2025 URGENT Challenge which aims to bring more attention to constructing Universal, Robust and Generalizable speech EnhancemeNT models.

LDC will post conference updates via our social media platforms. We look forward to seeing you in Rotterdam! 

Fall 2025 LDC data scholarship program 
Student applications for the Fall 2025 LDC data scholarship program are being accepted now through September 15, 2025. This program provides eligible students with no-cost access to LDC data. Students must complete an application consisting of a data use proposal and letter of support from their advisor. For application requirements and program rules, visit the LDC Data Scholarships page


New publications:

Mixer 6 - CHiME 8 Transcribed Calls and Interviews was developed for the 7th and 8th CHiME (Computational Hearing in Multisource Environments) challenges. It contains 80 hours of English interviews and telephone speech from Mixer 6 Speech (LDC2013S03) with transcripts developed for the CHiME challenges divided into training, development and test sets. This data was used in CHiME 7 Task 1 and CHiME 8 Task 1 both of which focused on transcription and segmentation across varied recording conditions such as interviews, meetings, and dinner parties, with an emphasis on generalization across recording device types and array topologies.

The data includes audio from Mixer 6 Speech recorded on 13 microphones for a total of 1063 hours (corresponding to 80 hours of speech). The development and test sets are speaker-disjoint from the training data and consist of fully transcribed, multi-microphone interviews. Each transcript segment was labeled with the speaker, the uttered text, and the start and end times in seconds for that segment. 

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

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Abstract Meaning Representation 2.0 - Machine Translations was developed at the University of Edinburgh, School of Informatics and the University of Zurich, Department of Computational Linguistics. It consists of Spanish, German, Italian and Mandarin Chinese automatic translations of the source English and professionally-translated Spanish, German, Italian and Mandarin Chinese sentences in Abstract Meaning Representation 2.0 - Four Translations (LDC2020T07). The translations were collected through Google Translate between May 2018 and March 2024.

The source English sentences are a subset (1,371 sentences) of the sentences contained in Abstract Meaning Representation (AMR) Annotation Release 2.0 (LDC2017T10), a semantic treebank of over 39,000 English natural language sentences from broadcast conversations, newswire and web text.

Translations were from each of the five languages (English, Spanish, German, Italian and Mandarin Chinese) to the other four languages (Spanish, German, Italian and Mandarin Chinese) covering 20 language pairs. The dataset contains 1371 source sentences in each language, each with a professionally translated source sentence and multiple dated translations by Google Translate.

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

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KARIOS Phase 1 Quizlet was developed by LDC and contains English and Spanish text, video and image data and annotations used for pre-evaluation research and system development during Phase 1 of the DARPA KAIROS program. KAIROS Quizlets were a series of narrowly defined tasks designed to explore specific evaluation objectives enabling KAIROS system developers to exercise individual system components on a small data set prior to the full program evaluation. This corpus contains the complete set of Quizlet data used in Phase 1 which focused on two real-world complex events (CEs) within the Improvised Explosive Device bombing scenario: CE1001 (2018 Caracas drone attack) and CE1002 (Utah High School backpack bombing).

Source data was collected from the web; 30 root web pages were collected and processed, yielding 29 text data files, 216 image files and 5 video files. Annotation steps included labeling scenario-relevant events and relations for each document to develop a structured representation of temporally ordered events, relations and arguments and generating a reference knowledge graph.

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.