Generative poetry

Concept
Pronunciation

Understanding ARPABET Pronunciation

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The pronunciation guide uses the ARPABET phonetic system—the same system used in speech recognition and text-to-speech applications.

Vowel Examples:
AE1 = cat, bat
EH1 = bed, head
IY1 = see, me
OW1 = go, boat
UW1 = boot, do
Stress Numbers:
0 = no stress (unstressed)
1 = primary stress (loud)
2 = secondary stress (medium)
Example:
AH0 TH IY1 N AH0
= a-THEE-na (Athena)

The stressed syllable (marked with 1) is pronounced louder and clearer than others.

Quick Definition

Poetry created through evolving, rule-based, or algorithmic processes

Detailed Definition
Generative poetry employs algorithmic, procedural, or rule-based methods—often using digital tools or constrained writing techniques—to create verse where form emerges from systematic processes rather than authorial intention alone; rooted in Oulipo and contemporary digital poetics, this approach explores the intersection of chance, structure, and language, producing texts that challenge notions of authorship, meaning, and poetic spontaneity.
Example
Example in poetry:
John Cage’s mesostics generate poems from source texts using chance operations; Nanni Balestrini’s computer-generated poetry rearranges news text; Allison Parrish’s "Articulations" uses algorithms to create verse; Jackson Mac Low’s diastics produce poems by selecting letters from a seed text; Oulipo writers like Queneau use constrained generative techniques (e.g., "Hundred Thousand Billion Poems").
Additional Notes
Generative poetry uses algorithms, chance operations, or rule-based systems to create text—rooted in Oulipo, Dada, or digital poetics (e.g., Queneau’s “Hundred Thousand Billion Poems”). It questions authorship and explores language’s combinatorial potential. Students should analyze the constraints: how do rules shape meaning? Is the output poetic or conceptual? Related to “technical lexicon” in its procedural focus.
Also Known As
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