First DIHARD Challenge Evaluation - SEEDLingS

Item Name: First DIHARD Challenge Evaluation - SEEDLingS
Author(s): Neville Ryant, Mark Liberman, James Fiumara, Christopher Cieri
LDC Catalog No.: LDC2019S13
ISBN: 1-58563-888-9
ISLRN: 096-549-178-318-5
Release Date: July 15, 2019
Member Year(s): 2019
DCMI Type(s): Sound, Text, Software
Sample Type: pcm
Sample Rate: 16000
Data Source(s): microphone speech
Application(s): speech activity detection, diarization
Language(s): English
Language ID(s): eng
License(s): First DIHARD Challenge - SEEDLingS Agreement (For-Profit)
First DIHARD Challenge - SEEDLingS Agreement (Non-Member)
First DIHARD Challenge - SEEDLingS Agreement (Not-For-Profit)
Online Documentation: LDC2019S13 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Ryant, Neville, et al. First DIHARD Challenge Evaluation - SEEDLingS LDC2019S13. Web Download. Philadelphia: Linguistic Data Consortium, 2019.
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First DIHARD Challenge Evaluation - SEEDLingS was developed by Duke University and the Linguistic Data Consortium (LDC) and contains approximately two hours of English child language recordings along with corresponding annotations used in support of the First DIHARD Challenge.

The First DIHARD Challenge was an attempt to reinvigorate work on diarization through a shared task focusing on "hard" diarization; that is, speech diarization for challenging corpora where there was an expectation that existing state-of-the-art systems would fare poorly. As such, it included speech from a wide sampling of domains representing diversity in number of speakers, speaker demographics, interaction style, recording quality, and environmental conditions, including, but not limited to: clinical interviews, extended child language acquisition recordings, YouTube recordings, and conversations collected in restaurants.


The source data was drawn from SEEDLingS (The Study of Environmental Effects on Developing Linguistic Skills) corpus, designed to investigate how infants' early linguistic and environmental input plays a role in their learning. Recordings were generated in the home environment of infants in the Rochester, New York area. A subset of that data was annotated by LDC for use in the First DIHARD Challenge.

This release, when combined with First DIHARD Challenge Evaluation - Nine Sources (LDC2019S12), contains the evaluation set audio data and annotation as well as the official scoring tool. The development data for the First DIHARD Challenge is also available from LDC as Eight Sources (LDC2019S09) and SEEDLingS (LDC2019S10).

All audio is provided in the form of 16 kHz, mono-channel FLAC files. The diarization for each recording is stored as a NIST Rich Transcription Time Marked (RTTM) file. RTTM files are space-separated text files containing one turn per line. Segmentation files are stored as HTK label files. Each of these files contains one speech segment per line. Both of the annotation file types are encoded as UTF-8. More information about the file formats is provided in the included documentation.


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