Generating text with recurrent neural networks

I built a recurrent neural network trained to generate text in the style of Shakespeare, as well as some other data (recipes, online tech blogs). See the GitHub repository, which has training data and a Jupyter notebook.

Example: Shakespeare-style

Sentences often aren’t grammatical and made-up words pop up frequently, but the RNN has learned the script structure of Shakespeare’s writing well. (In some way this is pretty fitting for Shakespeare.) Without memory/attention built into this model, though, it’s hard for it to be consistent in terms of things like the characters in the generated works.

ROMEO: Did use thee fair?

BENVOLIO: Do count us grand it: but ‘tis well: In truth, sir; but the common rack with oath! Tendering me to the garteous labour.

WARWICK: I I last to-day, the vanity and double on the human car above that gamps about, And were her lips, how he not heard The gamporr’s maintily woo’d amazed: the unacowned silence Upon their very house; thou hast Wasted to thyself, but so defend thee. CLIFFORD: Come, couna with me well, and both be so long, ‘Waving their fortune’s to that Bolingbroke Hath throw’d to harve thee as we do.

POMPEY: Plentague, my lord; and weep you plain, I would know

KING RICHARD III: Look on her! not a warning sense.

TRANIO: Now is the Vincentio.

BAPTISTA: And I could wish I do welcome for it.

JULIET: Hath been God’s knigns; we are comforter, no more; Amen, amaz, to put Both obedient heir A hope to give against yourself in thing, And most cheer to the Tarquis rinisher.

GLOUCESTER: At that may be! Be as this own vassal hands, will you seek to do.