oai:www.ldc.upenn.edu:LDC2023V01
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OLAC Record oai:www.ldc.upenn.edu:LDC2023V01 |
| Metadata | ||
| Title: | 2019 NIST Speaker Recognition Evaluation Test Set -- Audio-Visual | |
| Access Rights: | Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining | |
| Bibliographic Citation: | Sadjadi, Omid, et al. 2019 NIST Speaker Recognition Evaluation Test Set -- Audio-Visual LDC2023V01. Web Download. Philadelphia: Linguistic Data Consortium, 2023 | |
| Contributor: | Sadjadi, Omid | |
| Greenberg, Craig | ||
| Li, Xuansong | ||
| Strassel, Stephanie | ||
| Date (W3CDTF): | 2023 | |
| Date Issued (W3CDTF): | 2023-02-15 | |
| Description: | *Introduction* 2019 NIST Speaker Recognition Evaluation Test Set -- Audio-Visual was developed by the Linguistic Data Consortium (LDC) and NIST (National Institute of Standards and Technology). It contains approximately 64 hours of English audio-visual data for development and test, answer keys, enrollment, trial files and documentation from the NIST-sponsored 2019 Speaker Recognition Evaluation (SRE). The ongoing series of SRE yearly evaluations conducted by NIST are intended to be of interest to researchers working on the general problem of text independent speaker recognition. To this end the evaluations are designed to be simple, to focus on core technology issues, to be fully supported and to be accessible to those wishing to participate. The 2019 evaluation task was speaker detection, that is, to determine whether a specified target speaker was speaking during a segment of speech. The evaluation was conducted in two parts: (1) a leaderboard-style challenge based on conversational telephone speech from LDC's Call My Net 2 corpus; and (2) a separate evaluation using audio-visual data collected by LDC for the VAST (Video Annotation for Speech Technology) project. Further information about the 2019 evaluation is contained in the evaluation plan included in this release. *Data* The VAST collection focused on amateur video recordings from various online media hosting services. The recordings vary in duration from 17.5 seconds to 13 minutes. Videos are encoded/compressed as mp4 files. Audio tracks are in aac format with a sample rate of 44.1 KHz; most have two audio channels (stereo), but some are monophonic (one channel). *Samples* Please view these samples: Video (mp4) Bounding Box (tsv) Diarization (tsv) *Updates* None at this time. | |
| Extent: | Corpus size: 16384392 KB | |
| Format: | Sampling Rate: 44100 | |
| Sampling Format: mp4 | ||
| Identifier: | LDC2023V01 | |
| https://catalog.ldc.upenn.edu/LDC2023V01 | ||
| ISLRN: 470-750-139-731-6 | ||
| DOI: 10.35111/pqkt-6r56 | ||
| Language: | English | |
| Language (ISO639): | eng | |
| License: | LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf | |
| Medium: | Distribution: Web Download | |
| Publisher: | Linguistic Data Consortium | |
| Publisher (URI): | https://www.ldc.upenn.edu | |
| Relation (URI): | https://catalog.ldc.upenn.edu/docs/LDC2023V01 | |
| Rights Holder: | Portions © 2011-2018 Google LLC, © 2020, 2023 Trustees of the University of Pennsylvania | |
| Type (DCMI): | MovingImage | |
| Text | ||
| Type (OLAC): | primary_text | |
OLAC Info |
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| Archive: | The LDC Corpus Catalog | |
| Description: | http://www.language-archives.org/archive/www.ldc.upenn.edu | |
| GetRecord: | OAI-PMH request for OLAC format | |
| GetRecord: | Pre-generated XML file | |
OAI Info |
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| OaiIdentifier: | oai:www.ldc.upenn.edu:LDC2023V01 | |
| DateStamp: | 2023-12-05 | |
| GetRecord: | OAI-PMH request for simple DC format | |
Search Info | ||
| Citation: | Sadjadi, Omid; Greenberg, Craig; Li, Xuansong; Strassel, Stephanie. 2023. Linguistic Data Consortium. | |
| Terms: | area_Europe country_GB dcmi_MovingImage dcmi_Text iso639_eng olac_primary_text | |