Contextual Speech Recognition Using Deep Learning

This paper introduces a deep learning-based approach to improve speech recognition accuracy, especially in noisy environments or when dealing with variations in speech. It uses deep neural networks to model the context of the speech signal, allowing the system to better understand and transcribe spoken words. This is achieved by training the network to predict acoustic features based on context, then incorporating these predictions into the speech recognition process, ultimately enhancing the accuracy and robustness of the system.