The Future of Digital Media - Prof. K.H. Brandenburg - Media In Transition 2007

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Prof. Brandenburg, inventor of the MP3 Standard, speaks about Innovation at Fraunhofer Institute for Digital Media Technology

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The Future of Digital Media - Prof. K.H. Brandenburg - Media In Transition 2007

  1. 1. The Future of Media Technologies Karlheinz Brandenburg Technische Universität Ilmenau, Institut für Medientechnik Fraunhofer Institut für Digitale Medientechnologie September, 2007 Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 1
  2. 2. Overview • Old dreams, new reality • Scenarios of media use – The “home stereo” of tomorrow • To DRM or not to DRM ? • Rich Media Management • Conclusions Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 2
  3. 3. What is going on in consumer electronics ? • Digital TV – Still not in the majority of homes • Internet Audio – On all computers, 40% of people us it – For Christmas, mp3 players are on the top spot of childrens wish lists ☺ • Music from all around – There is serious competition for radio • DVD Audio / SACD – Where are they ? Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 3
  4. 4. What is happening to the „old media“ ? • For the first time in 50 years: the average time young people spent in front of the TV screen is decreasing • Radio looses a substantial amount of listeners, especially among young people • People spend more money on computer games • Record companies and Hollywood studios complain about less business Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 4
  5. 5. Global trends: Quantity leads to paradigm changes • The number of TV programs: –1 –5 – 35 – 300 – 3000 • How do I find my favorite program ? • EPGs, web sites, communities, Podcasts • Example: MusicMatch Radio: Radio or not ? Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 5
  6. 6. Global trends: Global reach for special interests • Special interests find their – Web sites – Music – Video – Discussion place on the Web • Just 100 people can establish a well organised global group • Blogs, fora, chat rooms, cooperative computer games create virtual worlds Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 6
  7. 7. New equipment (this was never sold) Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 7
  8. 8. Where are my multimedia data ? • Physically stored in my home (CD, DVD) • On my home server • On my PDA or mobile phone • Detached on the net • Just recreated from metadata whenever I need them Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 8
  9. 9. Examples: The future home stereo setup (really ?? ☺) Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 9
  10. 10. The home stereo of tommorow: • Remembers my music: – Each CD gets ripped just when I play it • Helps to search for my favorite music – “query by humming” – Look for certain genres – Searches the Internet – Where can I listen to / buy this music ? • Helps to assemble my favorite music playlist – What is similar, but new ? – “please play my favorite music for this time of the day” Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 10
  11. 11. To DRM or not to DRM ☺ • Ideas for protected media content have been around since the mid 90s • Early systems lacked sophistication • SDMI – Initiated by the music industry – Work on requirements for DRM systems – Success or failure ? • Current systems: – Windows DRM – Fairplay – OMA 1.0, 2.0 – Music distribution without DRM Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 11
  12. 12. Requirements for successful applications: • Ease of use: – work everywhere, on all equipment = interoperability • Add value: – digital is more than just the same product add-on text / pictures / video / special sale etc. • Make illegal use more difficult – enough copy protection to make piracy a conscious decision Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 12
  13. 13. Basic Building Blocks and Concepts • Secure envelope • Scrambling / encryption • Robust embedding of data (watermarking) • Authentication – User authentication – “Bind to”, authenticate content • Secure Authenticated Channel • Super Distribution Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 13
  14. 14. User expectations • For personal use, music (on Redbook CD) can be – moved (from home stereo to the car) – copied (for example to tape) – shared between family members – lent to my best friend • All compliant CDs used to play on all equipment with the same physical form factor (interoperability) • Current technology (mp3) allows all of the above • Secure Electronic Music Distribution (EMD) has to meet these expectations Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 14
  15. 15. PotatoSystem – Alternative Approach to Music Distribution • Innovative and flexible alternative for artists and labels to sell music using MP3 • Applies neither copy protection nor DRM • Customers can super-distribute the purchased music via their websites and receive a commission • Provides many useful features: – Accounting with collecting societies – Individual design of online musicshops – Selling music on MySpace Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 15 4FriendsOnly.com Internet Technologies AG
  16. 16. Selling with the PotatoSystem • Artists, labels or download portals provide their files on their own servers • They register the songs in the PotatoSystem (via web form or Excel file upload) • They are free in choosing price and currency • The PotatoSystem provides an applicable iFrame for each registered file or album Revenue splitting 43% – 78% Proportion for original suppliers (labels, artists and portals) depending on resellers level 5% – 35% Commissions for resellers (depending on reseller level) 17% Transaction costs (payment, licence fees) 5% PotatoSystem Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 16 4FriendsOnly.com Internet Technologies AG
  17. 17. Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 17
  18. 18. Rich Media Management Multimodal metadata retrieval • Context-based metadata creation (User, Usage) • Content-based metadata creation (Rhythm, Genre, Mood, Harmony, .. ) Storage of feature vectors and textual metadata Machine learning (Clustering, context adaptation,..) Supports content-based/semantic queries Allows for a lot of new services & applications Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 18
  19. 19. How to gather metadata ? – Expert knowledge, deploying the public, Sources metadata services (CDDB, FreeDB) – Context-derived, collaborative filtering – Automated extraction of relevant features Content-derived from the content data – Find clusters in the high-dimensional feature space that represent semantic properties or similarities – Efficient algorithms ( »embedded«) Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 19
  20. 20. Multimedia Information Retrieval – available technologies Recognition, – AV-recognition (AudioID, PhotoID, VideoID) Similarity – AV-similarity (Soundslike, PhotoID) – Song-segmentation Semantic Analysis – Genre classifikation (GenreID), Speech-/Music discrimination – Dominant melody transcription, Query by Humming (QbH) – Bass transcription – Tempo-, beat determination – Drum pattern transcription – Harmony transcription – Face-, object detection & identification – (Lead-) instrument recognition – Singer detection and characterization Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 20
  21. 21. AudioID Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 21
  22. 22. AudioID – the basic idea Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 22
  23. 23. Query by Humming at Saturn-Markt, München Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 23
  24. 24. MIR-Technologies – Music Segmentation • Inner-song similarities / dissimilarities based on a set of low-level audio features • Measure of innovation • Segment classification (verse, chorus) Intelligent navigation within songs • Retrieval of most significant part of a song (“audio-thumbnail”) • Basis for a deeper semantic analysis of the segments (lead instrument, vocals, etc. ) Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 24
  25. 25. AudioID – Sonos: Modeling Perceptual Music Similarities Holistic • Each song represents just one single class • Use distance metric from a holistic feature space (e.g. vs. euclidian distance) too simple! Modular • Each song exhibits certain semantic properties (aspects) classification • Measure the aspect qualities and build an aspect-profile approach • Translate audio content into the semantic space Select aspects according to their perceptual relevancy objective subjective • genre affiliation • mood: happy vs. sad • drums vs. no drums • aggressive vs. • singer vs. no singer calmative • slow vs. fast Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 25
  26. 26. Conclusions • The age of digital media has just started • Signal processing brings us a lot of new possibilities for future home multimedia devices • Searching and recommendation are crucial applications for tommorow‘s media architectures • For distribution of media: win your consumers with reasons why to buy Prof. Karlheinz Brandenburg, bdg@iis.fraunhofer.de Page 26

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