Two distinct approaches to algorithmic poetry generation. Volta uses context-free grammar for structured, rule-based composition, while Poetry a la Markov employs probabilistic text modeling trained on classic verse. Both systems generate rhyming poems following customizable schemes.
Uses context-free grammar to generate syntactically correct sentences with proper structure. Pre-defined sentence patterns ensure varied and natural-sounding poetic lines.
Builds a Markov chain from a corpus of classic poetry, then generates new lines that statistically resemble the training data while following rhyme schemes.
Alternate
Couplet
Enclosed
Terza Rima
Any pattern
Both systems use APIs like Datamuse for phonetic analysis, ensuring generated poems have proper end-rhymes matching the chosen scheme.
The Markov approach is trained on thousands of lines of classic poetry to capture meter, vocabulary, and natural language flow.
Volta uses context-free grammar with expandable rules to produce syntactically valid sentences that can be tuned for style.