The problem MyVoice solves

Individuals with hearing impairments often face communication barriers that limit their ability to engage in meaningful conversations and participate fully in social interactions.

Traditional methods like sign language interpretation or written communication may not always be accessible or efficient, leading to frustration and isolation for those with hearing impairments and their communication partners.

Challenges we ran into

Data Collection and Annotation: Gathering comprehensive datasets of sign language gestures for training our Machine Learning models required meticulous attention to detail. Accurate annotation and labeling of these datasets were essential for effective model training.

Model Optimization: Fine-tuning our Machine Learning models to accurately interpret a wide range of sign language gestures was a priority. This involved experimenting with model parameters, optimizing algorithms, and addressing issues related to overfitting and generalization.

Cross-Cultural Adaptability: Ensuring that "MyVoice" was culturally sensitive and adaptable to diverse sign language variations and communication styles was a key focus. Collaboration with sign language experts and communities helped incorporate cultural nuances and promote inclusivity.