Monday, November 8, 2010

Crowdsourcing, Collaboration, Creativity, and Complexity

Speaker: Aniket Kittur, HCII
Location: GHC 4405
Date: Nov 10, 2010 at Noon

Title: Crowdsourcing, Collaboration, Creativity, and Complexity

The talk will focus on the three following topics:
- Towards a model of workers on Mechanical Turk, aka, how to get your work done and done well
- Truly collaborative crowdsourced translation
- Crowdforge: applying principles from distributed computing to crowdsource complex work

Speaker Bio:

Aniket Kittur is an Assistant Professor in the Human-Computer
Interaction Institute at Carnegie Mellon. He received his Ph.D. in
Cognitive Psychology from UCLA studying the cognitive processes
underlying sensemaking activities such as learning, memory, and
insight. His research focuses on harnessing the efforts of many
individuals to make sense of information together in ways that exceed
their individual cognitive capacities, including domains such as
Wikipedia, crowdsourcing markets, and scientific collaboration. His
research employs multiple complementary techniques, including
empirical experiments, statistical and computational modeling,
visualization, data mining, and machine learning.

Wednesday, September 8, 2010

Crowdsourcing for Machine Translation

Speaker: Vamshi Ambati
Location: GHC 4405
Date: September 12, 2010: Noon

Slides: http://bit.ly/crowdtalk [pdf]

Abstract:
Machine Translation for low-resource languages has not received wide attention, primarily due to lack of existing parallel corpora, or access to language experts that can create such resources. In this talk, I will share our experience with using crowd-sourcing platforms like Mechanical Turk for reaching bilingual speakers on the web. We will discuss the design of the task for effective elicitation from the crowd.

When working with crowd data, the objectives are two-fold - maximizing the quality of data from multiple non-experts, and minimizing the cost of annotation by pruning noisy annotators. I will discuss our recent experiments in Machine Translation for selection of high quality crowd translations by explicitly modeling annotator reliability based on agreement with other submissions. I will also present some preliminary results in cost minimization and report their adaptation and feasibility to machine translation.

Tuesday, June 8, 2010

CrowdFlower platform for crowdsourcing

Speaker: Lukas Biewald, CEO CrowdFlower
Date: July 27, 2010 at Noon
Location: NSH 3305