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CAMIO: A Corpus for OCR in Multiple Languages
CAMIO (Corpus of Annotated Multilingual Images for OCR) is a new corpus created by Linguistic Data Consortium to serve as a resource to support the development and evaluation of optical character recognition (OCR) and related technologies for 35 languages across 24 unique scripts.
Optical Character Recognition
Optical Character Recognition (OCR)
The 2022 NIST Language Recognition Evaluation
In 2022, the U. S. National Institute of Standards and Technology (NIST) conducted the latest Language Recognition Evaluation (LRE) in an ongoing series administered by NIST since 1996 to foster research in language recognition and to measure state-of-the-art technology.
The 2021 NIST Speaker Recognition Evaluation
Evaluation results indicate: audio-visual fusion produce substantial gains in performance over audio-only or visual-only systems; top performing speaker and face recognition systems exhibited comparable performance under the matched domain conditions present in this evaluation; and, the use of complex neural network architectures (e. g., ResNet) along with angular losses with margin, data augmentation, as well as long duration fine-tuning contributed to notable performance improvements for the audio-only speaker recognition task.
The NIST CTS Speaker Recognition Challenge
The US National Institute of Standards and Technology (NIST) has been conducting a second iteration of the CTS challenge since August 2020.
