Multimodality, interactivity, and crowdsourcing for document transcription
نویسندگان
چکیده
منابع مشابه
Crowdsourcing Transcription Beyond Mechanical Turk
While much work has studied crowdsourced transcription via Amazon’s Mechanical Turk, we are not familiar with any prior cross-platform analysis of crowdsourcing service providers for transcription. We present a qualitative and quantitative analysis of eight such providers: 1888-Type-It-Up, 3Play Media, Transcription Hub, CastingWords, Rev, TranscribeMe, Quicktate, and SpeakerText. We also provi...
متن کاملCrowdsourcing Document Relevance Assessment with Mechanical Turk
We investigate human factors involved in designing effective Human Intelligence Tasks (HITs) for Amazon’s Mechanical Turk. In particular, we assess document relevance to search queries via MTurk in order to evaluate search engine accuracy. Our study varies four human factors and measures resulting experimental outcomes of cost, time, and accuracy of the assessments. While results are largely in...
متن کاملUsing Crowdsourcing to Compare Document Recommendation Strategies for Conversations
This paper explores a crowdsourcing approach to the evaluation of a document recommender system intended for use in meetings. The system uses words from the conversation to perform just-in-time document retrieval. We compare several versions of the system, including the use of keywords, retrieval using semantic similarity, and the possibility for user initiative. The system’s results are submit...
متن کاملMultimodality and Interactivity: Connecting Properties of Serious Games with Educational Outcomes
Serious games have become an important genre of digital media and are often acclaimed for their potential to enhance deeper learning because of their unique technological properties. Yet the discourse has largely remained at a conceptual level. For an empirical evaluation of educational games, extra effort is needed to separate intertwined and confounding factors in order to manipulate and thus...
متن کاملA Transcription Task for Crowdsourcing with Automatic Quality Control
In this paper, we propose a two-stage transcription task design for crowdsourcing with an automatic quality control mechanism embedded in each stage. For the first stage, a support vector machine (SVM) classifier is utilized to quickly filter poor quality transcripts based on acoustic cues and language patterns in the transcript. In the second stage, word level confidence scores are used to est...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Intelligence
سال: 2018
ISSN: 0824-7935
DOI: 10.1111/coin.12169