REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of priority under 35 U.S.C. § 119 to Russian Patent Application No. RU2019109198, filed Mar. 29, 2019, the disclosure of which is incorporated by reference herein.

The present application is related to U.S. patent application Ser. No. 16/137,981, entitled “TRAINING IMAGE-PROCESSING NEURAL NETWORKS BY SYNTHETIC PHOTOREALISTIC INDICIA-BEARING IMAGES,” filed Sep. 21, 2018, which is assigned to the assignee of the present application and is hereby incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure is generally related to computer systems, and is more specifically related to systems and methods for generating text corpora comprising realistic optical character recognition (OCR) errors and training language models using the text corpora.

BACKGROUND

Optical character recognition (OCR) process may extract computer-readable and searchable textual information from indicia-bearing images of various media (such as printed or handwritten paper documents, banners, posters, signs, billboards, and/or other physical objects bearing visible text symbols (including encoded text symbols, such as barcodes) on one or more of their surfaces). Before being fed to an OCR process, input images may be pre-processed by one or more convolutional neural networks which correct certain image defects.

SUMMARY OF THE DISCLOSURE

In accordance with one or more aspects of the present disclosure, an example method of training image processing neural networks by synthetic photorealistic indicia-bearing images may comprise: generating, by a computer system, an initial set of images based on an input text corpus comprising text; overlaying, by the computer system, one or more simulated defects over the initial set of images to generate an augmented set of images comprising text segments; generating an output text corpus based on the augmented set of images; and training, using the output text corpus, a language model for optical character recognition.

In accordance with one or more aspects of the present disclosure, an example system for training image processing neural networks by synthetic photorealistic indicia-bearing images may comprise: a memory; a processing device, coupled to the memory, the processing device configured to: generate an initial set of images based on an input text corpus comprising text; overlay one or more simulated defects over the initial set of images to generate an augmented set of images comprising text segments; generate an output text corpus based on the augmented set of images; and train, using the output text corpus, a language model for optical character recognition.

In accordance with one or more aspects of the present disclosure, an example computer-readable non-transitory storage medium may comprise executable instructions that, when executed by a processing device, cause the processing device to: generate an initial set of images based on an input text corpus comprising text; overlay one or more simulated defects over the initial set of images to generate an augmented set of images; generate an output text corpus based on the augmented set of images; and train, using the output text corpus, a language model for optical character recognition.

