Mental models: towards a cognitive science of language, inference, and consciousness
Mental models: towards a cognitive science of language, inference, and consciousness
Listening skills development through multimedia
Journal of Educational Multimedia and Hypermedia
Information Retrieval
Cultural differences explaining the differences in results in GSS: implications for the next decade
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Collaborative translation by monolinguals with machine translators
Proceedings of the 14th international conference on Intelligent user interfaces
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Cheap, fast and good enough: automatic speech recognition with non-expert transcription
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Crowdsourcing and language studies: the new generation of linguistic data
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
A visualized communication system using cross-media semantic association
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
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As video-sharing websites such as YouTube proliferate, the ability to rapidly translate video clips into multiple languages has become an essential component for enhancing their global reach and impact. Moreover, the ability to provide closed captioning in a variety of languages is paramount to reach a wider variety of viewers. We investigate the importance of visual context clues by comparing transcripts of multimedia clips (which allow transcriptionists to make use of visual context clues in their translations) with their corresponding written transcripts (which do not). Additionally, we contrast translations produced using crowdsourcing workers with those made by professional translators on cost and quality. Finally, we evaluate several genres of multimedia to examine the effects of visual context clues on each and demonstrate the results through heat maps.