Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
The Great Language Game
Search
Lars Yencken
September 02, 2013
Programming
340
0
Share
The Great Language Game
A brief introduction to the Great Language Game, given to the Melbourne Python User Group.
Lars Yencken
September 02, 2013
More Decks by Lars Yencken
See All by Lars Yencken
Linguistics, a whirlwind tour!
larsyencken
0
63
Pycon 2014 Recap
larsyencken
0
73
Nine months of food
larsyencken
0
300
Automation for web development
larsyencken
0
160
Scaling a web stack
larsyencken
4
210
Similarity metrics for Japanese kanji
larsyencken
0
88
Other Decks in Programming
See All in Programming
Road to RubyKaigi: Play Hard(ware)
makicamel
1
470
Terraform言語の静的解析 / static analysis of Terraform language
wata727
1
110
Surviving Black Friday: 329 billion requests with Falcon!
ioquatix
0
830
実践CRDT
tamadeveloper
0
590
Agentic Elixir
whatyouhide
0
410
AIを導入する前にやるべきこと
negima
2
250
[RubyKaigi 2026] Require Hooks
palkan
1
230
HTML-Aware ERB: The Path to Reactive Rendering @ RubyKaigi 2026, Hakodate, Japan
marcoroth
0
290
Server-Side Kotlin LT大会 vol.18 [Kotlin-lspの最新情報と Neovimのlsp設定例]
yasunori0418
1
190
年間50登壇、単著出版、雑誌寄稿、Podcast出演、YouTube、CM、カンファレンス主催……全部やってみたので面白さ等を比較してみよう / I’ve tried them all, so let’s compare how interesting they are.
nrslib
4
800
Liberating Ruby's Parser from Lexer Hacks
ydah
2
2.2k
AWSコミュニティ活動は顧客のクラウド推進に効くのか / Do AWS community activities help customers adopt the cloud?
seike460
PRO
0
150
Featured
See All Featured
The AI Revolution Will Not Be Monopolized: How open-source beats economies of scale, even for LLMs
inesmontani
PRO
3
3.4k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
25
1.9k
The Curious Case for Waylosing
cassininazir
0
320
How to Align SEO within the Product Triangle To Get Buy-In & Support - #RIMC
aleyda
2
1.5k
ラッコキーワード サービス紹介資料
rakko
1
3.1M
Art, The Web, and Tiny UX
lynnandtonic
304
21k
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
21
1.5k
How to build an LLM SEO readiness audit: a practical framework
nmsamuel
1
720
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Future Trends and Review - Lecture 12 - Web Technologies (1019888BNR)
signer
PRO
0
3.5k
Site-Speed That Sticks
csswizardry
13
1.2k
From Legacy to Launchpad: Building Startup-Ready Communities
dugsong
0
200
Transcript
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . The Great Language Game Lars Yencken Melbourne Python User Group September 2, 2013
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . I’m a language geek
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . I’m a human language geek
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . The world has something like 7,000 languages
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . The world has something like 7,000 languages So many!
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . The world has something like 7,000 languages Too many to learn!
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . But... with the help of a lil Python we can at least learn to tell the difference between languages
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . Aside: langid.py Distinguish between languages in text form
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . Aside: langid.py Distinguish between languages in text form ผู้สื่อข่าวไทยวิเคราะห์นโยบายผู้ขอลี้ภัยพรรคต่างๆ >>> import langid >>> langid.classify(l.encode(’utf8’)) (’th’, 1.0) >>> langid.classify(’¡Venga hombre!’) (’es’, 0.5726778160604622)
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . First attempt: streaming radio ▶ There’s lots of internet radio out there! ▶ But it’s all in shitty old formats ▶ And Python support for decoding them all is not great ▶ Solution: sh module and mplayer ▶ Still too hard!
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . Second attempt: scrape SBS ▶ Podcasts News podcasts in about 70 languages ▶ Good quality recordings! ▶ (Sometimes) daggy Australian accents ▶ Fetching: pyquery, requests and parse ▶ Processing audio: wave + sh wrapping avconv and mp3gain ▶ Success!
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . Aside: sh Wraps shell calls like a boss! >>> from sh import ffmpeg >>> ffmpeg(’-i’, input_file, output_file) >>> from sh import mp3gain >>> mp3gain(’-r’, ’-k’, ’-t’, ’-s’, ’r’, sound_file)
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . More about languages ▶ Wikipedia: manual data entry ▶ Freebase API: via requests
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . End result: demo time!
. . . .. . . . .. . .
. .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . . .. . . . .. . . . .. . Thanks http://greatlanguagegame.com/