Polyglot: Distributed Word Representations for Multilingual NLP

Distributed word representations (word embeddings) have recently contributed to competitive performance in language modeling and several NLP tasks. In this work, we train word embeddings for more than 100 languages using their corresponding Wikipedias. We quantitatively demonstrate the utility of our word embeddings by using them as the sole features for training a part of speech tagger for a subset of these languages. We find their performance to be competitive with near state-of-art methods in English, Danish and Swedish. Moreover, we investigate the semantic features captured by these embeddings through the proximity of word groupings. We will release these embeddings publicly to help researchers in the development and enhancement of multilingual applications.Comment: 10 pages, 2 figures, Proceedings of Conference on Computational Natural Language Learning CoNLL'201

Catchment Care - Developing an Auction Process for Biodiversity and Water Quality Gains. Volume 1 - Report

This report describes the design, development and trial of catchment care. Catchment Care is an auction-based system which aims to increase the cost effectiveness of funds for private on-ground natural resource management actions.Water;Australia;Natural Resource Management;Catchment Care; auction.

Catchment Care - Developing an Auction Process for Biodiversity and Water Quality Gains. Volume 2 - Appendices

A Market-Based Instrument Pilot Project. Report to the Onkaparinga Catchment Water Management Board.Water;Australia;Natural Resource Management;Catchment Care; auction, market-based instruments.

The Expressive Power of Word Embeddings

We seek to better understand the difference in quality of the several publicly released embeddings. We propose several tasks that help to distinguish the characteristics of different embeddings. Our evaluation of sentiment polarity and synonym/antonym relations shows that embeddings are able to capture surprisingly nuanced semantics even in the absence of sentence structure. Moreover, benchmarking the embeddings shows great variance in quality and characteristics of the semantics captured by the tested embeddings. Finally, we show the impact of varying the number of dimensions and the resolution of each dimension on the effective useful features captured by the embedding space. Our contributions highlight the importance of embeddings for NLP tasks and the effect of their quality on the final results.Comment: submitted to ICML 2013, Deep Learning for Audio, Speech and Language Processing Workshop. 8 pages, 8 figure

The Tango Tokio

[Verse 1] Way out West, all over the golden gate, They’ve a tango, gee, but it’s simply great! Oh! oh! oh! oh! it’s the nicest tune, I know, It is called the Japanese glide away; You should see those Japanese slide away, When they play it, ev’rybody starts to sway it: [Chorus] Oh, oh, you Jap, little Jap, little Jap, little Japanese! Oh, oh, you cute little yap, little yap, little yapanese! How we live to see you prance, When they play that tango dance; It just puts us in a trance Oh, pinky panky poo, pinky panky poo! Oh, oh, you sly little, sly little, sly little Japaneses! You are a fly little, fly little, fly little Japanese! Tho’ you sometimes make us mad, If you want to make us glad, Do that teasing Tango Tokio. [Verse 2] When you hear that Tokio Tango tune, You’ll go dip, dip, dippy and pretty soon You’ll start swaying, just like this and just like that; You’ll imagine you are in Tokio, You will go clean clean off your kokio, If you know it, all day long you’d want to do it: [Chorus

Sometime, Someday, Somewhere

https://digitalcommons.library.umaine.edu/mmb-vp/4050/thumbnail.jp

I Didn\u27t Raise My Boy to Be a Soldier

VERSE 1Ten million soldiers to the war have gone,Who may never return again.Ten million mothers’ hearts must breakFor the ones who died in vain.Head bowed down in sorrowIn her lonely years,I heard a mother murmur thro’ her tears: CHORUS“I didn’t raise my boy to be a soldier,I brought him up to be my pride and joy,Who dares to place a musket on his shoulder,To shoot some other mother’s darling boy?Let nations arbitrate their future troubles,It’s time to lay the sword and gun away,There’d be no war today,If mothers all would say,“I didn’t raise my boy to be a soldier.” VERSE 2What victory can cheer a mother’s heart,When she looks at her blighted home?What victory can bring her backAll she cared to call her own.Let each mother answerIn the years to be,Remember that my boy belongs to me! CHORU

Billy, Billy, Bounce Your Baby Doll

https://digitalcommons.library.umaine.edu/mmb-vp/4336/thumbnail.jp