Podcasting De Luxe
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Transcript of Podcasting De Luxe
History and Development I
Past
•2006 – Start of Podcasting-ServiceSimple screening and audio recording with Camtasia – 50% failed First efforts for automated postprocessing
•2007 – Lifetime Podcasting1st Austrian Podcast Conference in cooperation with iUNIg
•2008 – Start with (live-)Streaming-ServiceLive Screening, audio and video recording on ePresence ServerCheck: http://curry.tugraz.at
•2009 – Start of iTunes U platform for TU GrazCheck: http://itunes.tugraz.at/series
•2010 – Start of Project: Automated Recording
•2011 – Searchable RecordingsStationary workflow version
History and Development II
Ongoing Developments and Future
•Since 2010 – Project: Automated Lecture RecordingsFocus: Workflow and usability improvement for recordingsFully automated recording and postprocessing of lectures
•Since 2011 – Searchable RecordingsFocus: Independent workflow versionDocumentation
•Since 2011 – Project: Automated Audio-Postprocessing:Cooperation with team from auphonic(http://auphonic.com/)
Didactics and Workflow I
Didactics and Purposes
•General Recordings (Screening / Audio / Video)Full Recording of lessonPre- or Postrecording at officeTutorial and instructional sequencesShort clips for help-center
•Live Streaming (Screening / Audio / Video)For Blended learningCasting of special events
•iTunes U„Selected“ media-files for Public Relations
Didactics and Workflow II
Workflow of General Recording
•FrameworkAgreement with teacher, recording details
•PreprocessCheck of hardware, software, lecture room conditionsWireless microphone, Tablet PCCamtasia, iShow U
•RecordingMinimal or full assistance
•PostprocessAudio OptimizationText to Search processingProduction of end-formats (Flash with Search, MP4)
•Publishingon TU Graz TeachCenter (LMS)
Overview
● Target: make long video presentation searchable
● Idea: generate index from extracted text
● Key Technology: OCR (Optical Character Recognition)
● Input: screen-capture video of presentation● Output: encoded video embedded in a flash
player with a ToC (Table of Contents) and a word search field [example]
Frame Extraction
● What software to use?
● Which frames to extract?
● Are all extracted frames useful?
Frame Extraction
Software: FFmpeg http://ffmpeg.org/
● Frame selection: FFmpeg (-vstats option)● Locate “I” frames● Extract timestamp
● Further frame sorting: Perl http://www.perl.org/
● Size● Position
OCR procedure
● Extracted frames are sent to OCR software for analysis
● OCR software returns one text file for each frame● Name of text file contains timing info
● Information from the test files is collected and used for ToC generation
Contact
TU Graz – Dept. Social Learning:Team PodcastingWalther NaglerYpatios Grigoriadis Christian StickelWolfgang Hauer
[email protected]@gmail.com Social Learning (TU Graz) sociallearning
http://elearning.tugraz.at