Application areas of RNNs

Some of the application areas where RNNs are used more often are as follows:

• Natural Language Modeling: The RNN models have been used in natural language processing (NLP) for natural language understanding and natural language generation tasks. In NLP, an RNN model is given a sequence of words and it predicts another sequence of words. Thus, the trained models can be used for generating the sequence of words, a field known as Text Generation. For example, generating stories, and screenplays. Another area of NLP is language translation, where given a sequence of words in one language, the model predicts a sequence of words in another language.
• Voice and Speech Recognition: The RNN models have great use in building models for learning from the audio data. In speech recognition, an RNN model is given audio data and it predicts a sequence of phonetic segments. It can be used to train the models to recognize the voice commands, or even for conversation with speech based...