Sign language translation using machine learning
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Globally, there are an estimated 70 million deaf individuals, with approximately 12 to 25 million using sign language as their primary mode of communication. Sign language has deep cultural significance and plays a role in shaping identity within deaf communities.
Sign languages are full, rich, natural languages with their own grammar, structure and expressive depth. They are as complex and capable as spoken or written languages, though they work differently. Spoken English is linear and word-based. In contrast, sign languages like British Sign Language (BSL) are visual and multidimensional. Sign languages use hand shapes, movement, facial expressions, body posture and space to convey meaning. This structure makes sign languages complex. Often, the meaning of a sign depends on context.