Image Feature Narrator for the Blind

Abstract

There are millions of visually impaired people in the world. The quality of life of visually impaired people is greatly affected by their inability to interpret visual text and images. For sighted people, the brain can recognize image features, but for blind people, this is not possible. So we create a model to help the computer identify features in the image. This model is a combination of recurrent neural networks (RNN), long short-term memory (LSTM), and convolutional neural networks (CNN). These deep learning algorithms use natural language processing to extract image attributes. Images are recognized using NLP, which uses natural language to describe images. In this chapter, we use CNNs and LSTMs (RNNs) to prepare a feature generator and use the gTTS API to listen to image details (Google Text To Speech). This API allows you to support multiple languages ​​and provide audio at a set rate.