Develop an Audio Sign Language Translator Using ML

Published on 14 May 2022. Written by Shirin Tikoo

Audio to Sign Language Translator using Python

Communication via gestures is a visual language that is utilized by hard of hearing and almost deaf individuals as their first language, it is additionally utilized by hearing people, for example, the individuals who experience difficulty with communicated in language because of an incapacity or condition individuals. To the extent a hard of hearing individual is concerned, approaching sign language communication is significant for their social, enthusiastic and semantic development. This framework is to help hearing-hindered individuals in India cooperate with others as it makes an interpretation of English text to Sign language.

SLNOTE

Audio to sign language translator using python - Project description

This task depends on changing the audio signals into text using speech to text APIs like Google API and afterward utilizing the semantics of Natural Language Processing, Machine Learning, Artificial Intelligence and Python for coding.

Python- Python is a broadly utilized general-purpose, high-level programming language. It allows programming in Object-Oriented and Procedural ideal models.

Artificial Intelligence – It is the theory and progression of PC frameworks to be able to perform tasks normally requiring human intelligence, for example, visual perception, speech recognition, decision-making, and interpretation between dialects.

Machine Learning – Machine learning is the study of getting PCs to act without being expressly modified. The Inputs are given as data sets by which the system learns and attempts to give the most ideal result to the user.

Natural Language Processing –It is the utilization of computational procedures for the analysis and synthesis of natural language and speech.

In this python project, we are going to use Indian sign language or American Sign Language data sets from google. The “Indian Sign Language” or ISL utilizes manual communication and non-manual communication to convey thoughts, emotions or feelings. ISL signs can be commonly grouped into three classes:

One-handed
Two-handed
Non-manual signs

One-handed signs and two-handed signs are additionally called manual signs where the signer uses his/her hands to make the signs for passing on the data whereas Non-Manual signs are produced by changing the body stance, outward appearances, and facial expressions.

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Project Implementation-

Initially, we take audio as input on a Personal Digital Assistant (PDA) by utilizing the python PyAudio module.
Next, we convert the audio to text using the Google Speech API.
Presently utilizing NLP i.e Natural language processing we breakdown the text into smaller, simpler and understandable text.
We have a reliance parser for analyzing the grammatical structure of the sentence and building up the connection between words.
By utilizing some AI we can prepare a model and now we have data sets of predefined sign language and ISL Generator can input sentences using ISL grammar rules.
By using AI we can display the converted audio into the sign.
Finally, we converted audio into Sign language.

Software Requirement

Programming language - OpenCV - Python

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Kit required to develop Develop an Audio Sign Language Translator Using ML:

Speaker

Technologies you will learn by working on Develop an Audio Sign Language Translator Using ML:

Develop an Audio Sign Language Translator Using ML

Audio to sign language translator using python - Project description

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