Authors :
Anshika Singh; Dr. Sharvan Kumar Garg
Volume/Issue :
Volume 8 - 2023, Issue 10 - October
Google Scholar :
https://tinyurl.com/4vw4pn6p
Scribd :
https://tinyurl.com/yn355de5
DOI :
https://doi.org/10.5281/zenodo.10057694
Abstract :
Handwriting recognition refers to interpreting
and analyzing handwritten text. In rece-nt years, there
have- been notable advance-ments in this field, espe-cially
in the context of computerize-d assessments. As online
e-xams and digital education platforms continue to gain
popularity, handwriting recognition plays a crucial role-
in evaluating students' written answers. Our proposed
system automatically recognizes and scores handwritten
responses on answer sheets by comparing them to the
correct answers provided by a moderator. To achieve
this, the system utilizes Optical Character Recognition
(OCR) to convert the handwritten text images into
computer-readable text. Additionally, BERT is employed
to convert the text into embeddings, and cosine similarity
is utilized to take these embeddings as input and provide
a final matching confidence score.
Keywords :
OCR, Google Vision OCR, BERT, Cosine similarity.
Handwriting recognition refers to interpreting
and analyzing handwritten text. In rece-nt years, there
have- been notable advance-ments in this field, espe-cially
in the context of computerize-d assessments. As online
e-xams and digital education platforms continue to gain
popularity, handwriting recognition plays a crucial role-
in evaluating students' written answers. Our proposed
system automatically recognizes and scores handwritten
responses on answer sheets by comparing them to the
correct answers provided by a moderator. To achieve
this, the system utilizes Optical Character Recognition
(OCR) to convert the handwritten text images into
computer-readable text. Additionally, BERT is employed
to convert the text into embeddings, and cosine similarity
is utilized to take these embeddings as input and provide
a final matching confidence score.
Keywords :
OCR, Google Vision OCR, BERT, Cosine similarity.
