Pentametron Reveals Unintended Poetry of Twitter Users
npr.org
npr.org
It seems possible, though certainly not easy, to mechanize some or all of that.
Then again, meaningful output isn't exactly necessary.[0]
(slight exaggeration, yes.)
I also think of the sci-fi short story Melancholy Elephants by Spider Robinson, which examines how perpetual copyright would negatively impact music (there are only so many novel melodies that are pleasant to listen to): http://www.baen.com/chapters/W200011/0671319744___1.htm
love watching people do the Harlem shake
I really really really want a snake
How does it work? I'm guessing it 1) scans tweets for pentameters using a large corpus annotated by syllables, then 2) looks up a rhyming dictionary to check the tweet is likely to be fruitful (i.e. doesn't end with the word orange or similar) and 3) waits...
for tweet in twitter_api.latest_tweets():
phonetic_tweet = convert_tweet_to_phonemes(tweet)
if is_iambic(phonetic_tweet):
end_rhymes = extract_end_rhymes(phonetic_tweet)
db.insert_iambic_tweet(tweet, end_rhymes)
for end_rhyme in end_rhymes:
rhyming_tweets = db.select_rhyming_tweets(end_rhyme)
if rhyming_tweets:
rhyming_tweet = random.choice(rhyming_tweets)
return [tweet, rhyming_tweet]
There are several open source word lists out there that make this feasible.https://github.com/darius/versecop
Pentametron is cooler. I did try filtering for rhymes too, but there wasn't enough data in the free feed, at least back then.
It'd automatically highlight syllable counts (and alternate the coloring of syllable-letter-groups within words). It'd indicate with bolding, underline, or other annotation stressed syllables. (Simple heuristics would get a lot right, and authors could correct the mistakes.) It could help with rhymes and near-rhymes. (I know there are already a lot of tools for this.)
Would make a nice web app.
Show HN: An IDE for poets (http://tranquillpoet.com) http://news.ycombinator.com/item?id=4775886