Copy-cat Bot for Narendra Modi which generates plausible new speeches in Modhi’s style using machine learning approaches

Abstract

Many consequences in the human past can be traced back to that one well-written, well-presented
speech. Speeches grasp the power to move nations or touch hearts as long as they are well-thought-out.
This is why gaining the expertise of speech giving and speech writing is something we should all intent to
gain. A copy-cat bot is a model that can learn the writing and talking style of a certain person and replicate
it. The main objective of this research study is to apply simple Recurrent Neural Network (RNN), Long
Short-Term Memory (LSTM) Recurrent Neural Networks and Gated Recurrent Unit (GRU) in developing
a speech generation system that deep learns one text and then generates new text. This research looks into
the generation of English transcripts of Narendra Modi’s speeches. The generated text using LSTM and
GRU models has great potential. The output resulted by RNN is less realistic and pragmatic, but its
variants LSTM and GRU performed better. Though the grammatical correctness and the sentence
transitions were absent in generated text of LSTM and GRU, but their output is somewhat logical as
compared to RNN. LSTM and GRU performed better as it generated more realistic text and training loss
is small, perplexity is small and mean probability is high compared to RNN.