AI Method for Converting Images to Speech Based on Long Short-Term Memory

Image captioning is the process of providing background information for an image. It is necessary to add captions to the images in the fields of processing massive amounts of unlabeled photographs and discovering hidden patterns in images. Image captioning is essential in many machine learning applications, including managing self-driving cars. Image captioning can be improved by using deep learning models and standard language processing; delivering subtitles for provided images is now simple. This research will make use of ResNet50, LSTM, DenseNet121, MobileNet, and MobileNetv2 when it comes to image subtitling. This research uses a recurrent neural network (long short-term memory) acting as a decoder and a convolution neural network (ResNet) acting as an encoder to generate captions for the images. For the benefit of the blind, this paper provides the visual content as text and translates it into voice for the specified image.