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In this newsletter:
LDC at Interspeech 2019
New Publications:
CALLFRIEND Canadian French Second Edition
BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training
Machine Reading Phase 1 NFL Scoring Training Data
LDC at Interspeech 2019
LDC is exhibiting at Interspeech 2019, September 15-19 in Graz, Austria. Stop by Booth F16 to learn more about recent developments at the Consortium and new publications.
Be on the lookout for The Second DIHARD Speech Diarization Challenge (DIHARD II), a special session co-organized by LDC, and the following presentations featuring LDC work:
The Second DIHARD Diarization Challenge: Dataset - task - and baselines
Neville Ryant, Christopher Cieri, Mark Liberman (LDC), Kenneth Church (Baidu, USA), Alejandrina Cristia (Laboratoire de Sciences Cognitives et Psycholinguistique), Jun Du (University of Science and Technology of China), Sriram Ganapathy (Indian Institute of Science)
Oral Session, Tuesday September 17, 10:00 – 10:20, Hall 3
Automatic Detection of Prosodic Focus in American English
Sunghye Cho and Mark Liberman (LDC), Yong-cheol Lee (Cheongju University)
Poster Session, Wednesday September 18, 16:00 – 18:00, Gallery B
Automatic detection of ASD in children using acoustic and text features from brief natural conversations
Sunghye Cho, Mark Liberman, Neville Ryant (LDC), Meredith Cola, Robert T. Schultz, Julia Parish-Morris (Children's Hospital of Philadelphia)
Oral Session, Wednesday September 18, 16:45 – 17:00, Hall 3
LDC will post conference updates via our Twitter feed and Facebook page. We hope to see you there!
New publications:
(1) CALLFRIEND Canadian French Second Edition was developed by LDC and consists of approximately 26 hours of unscripted telephone conversations between native speakers of Canadian French. This second edition updates the audio files to wav format, simplifies the directory structure, and adds documentation and metadata. The first edition is available as CALLFRIEND Canadian French (LDC96S48).
All data was collected before July 1997. Participants could speak with a person of their choice on any topic; most called family members and friends. All calls originated in North America. The recorded conversations last up to 30 minutes.
CALLFRIEND Canadian French Second Edition is distributed via web download.
2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $1000.
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(2) BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training was developed by LDC for the DARPA BOLT (Broad Operational Language Translation) program and consists of 388,027 words of Chinese and English parallel text enhanced with linguistic tags to indicate word relations.
This release consists of Chinese source text message and chat conversations collected using two methods: new collection via LDC's collection platform, and donation of SMS and chat archives from BOLT collection participants. The source data is released as BOLT Chinese SMS/Chat (LDC2018T15).
The BOLT word alignment task was built on treebank annotation. LDC automatically extracted Chinese source tokens, including empty categories/traces, from word-segmented files provided by the BOLT Chinese Treebank annotation team at Brandeis University. The word-segmented tokens were then used to automatically generate ctb (Chinese Treebank) alignment, as well as tokenized for character alignment by inserting white spaces to separate characters.
BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training is distributed via web download.
2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $1750.
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(3) Machine Reading Phase 1 NFL Scoring Training Data was developed by LDC for use in the DARPA (Defense Advanced Research Projects Agency) Machine Reading program. It contains 110 U.S. NFL (National Football League) scoring source documents and 110 standoff annotation files, manually annotated for instances of NFL Scoring annotation categories defined with respect to a NFL Scoring ontology.
The Machine Reading program aimed to develop automated reading systems to bridge the gap between knowledge contained in natural language texts and knowledge accessible to formal reasoning systems. The reading systems designed by program participants were required to extract and reason about facts from text in multiple domains.
The data in this release constitutes the training data for the NFL Scoring Use Cases evaluation, which tested the sports domain by extracting information about scoring events and game outcomes and aligning that information with an NFL Scoring ontology.
Machine Reading Phase 1 NFL Scoring Training Data is distributed via web download.
2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for $1000.
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