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Audiovisual content exploitation in the networked information society Roeland Ordelman Research&Development Netherlands Institute for Sound and Vision rordelman@beeldengeluid.nl
contents ,[object Object]
“Access”, an important keyword in the business models ...
... but what about access in practice
Technology and user interaction: from a ‘laboratory view’ on users to drawing them into the development chain,[object Object]
still growing:
digitally born television and radio programs made by the Dutch public broadcasting companies (video: 15K/hours/year)
PROARCHIVE: archiving service
selection of (Dutch) user generated content,[object Object]
Images of the Future ,[object Object]
One of the largest digitisation effort in Europe
Three goals:
Safeguarding heritage for future generations
Creating social- economical value (“unlock the social and economic potential of the collections”)
Innovation: new infrastructure for strengthening knowledge economy
To achieve these objectives, the cultural heritage sector is challenged to re-evaluate its business models,[object Object]
A strong business model is necessary to support this kind of investment and prove that such an investment will result in long-term socio-economic returns
The outcome of a Cost-Benefit analysis was positive: “The total balance of costs and returns of restoring, preserving and digitising audio-visual material (excluding costs of tax payments) will be between: 20+ and 60+ million.’’
Economic benefits:
Direct effects of the investment are revenues from sales, access for specific user groups, the repartition of copyright for the use of the material and so on.
The indirect effects concern the product markets and labour market.
Social benefits:
conservation of culture, reinforcement of cultural awareness, reinforcement of democracy through the accessibility of information, increase in multimedia literacy and contribution to the Lisbon goals set by the EUhttp://www.prestoprime.org/project/public.en.html
Content exploitation: from content is king ...
... to metadata rules
Manual annotation costly & limited
Research on automatic annotation ,[object Object]
visual features
information from audio
crowdsourcing
deploying collateral data sources:
subtitles, production scripts, meeting minutes, slides,[object Object]
work in progress ,[object Object]
national: development of common services
OAI, Persistent Identifiers, ASR service, Vocabulary Repositories
commercial: uptake by MNCs (Google and Microsoft) and SMEs
individual: bring about a shift regarding defensive attitude of content owners towards opening up their funded and protected archives (trust/reliability)  ,[object Object]
VidioActive, MultiMATCH, VIDI-video, LiWA, P2P-Fusion, Sterna, EUScreen, PrestoPrime
Collaboration agreement with Dutch research institutes
Researchers stationed at Sound and Vision
Provide data (TRECVID, VideoCLEF)
Research environment: exact copy of iMMix production environment for testing new technology
speech recognition
video analysis
fingerprinting

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Audiovisual Content Exploitation at FIA 15042010 NISV

Notes de l'éditeur

  1. The concept of technology-enhanced audiovisual indexing may have been a holy grail in earlier research, but recently it has become an urgent prerequisite in the context of our present-day information society. The effective exploitation of our Digital Libraries however, is currently impeded despite a wealth of technological progress. It becomes increasingly apparent that there may be an underlying problem, rooted in the disparity between technology and user needs. In order to respond to the demands of the information society advanced techniques and new workflow practices of use need to be explored by focusing on the needs of contemporary users, both professionals and non-professionals. At the same time, we need to foster opportunities for drawing user communities into the Digital Libraries, to involve them in enhancing content exploitability, e.g., by community tagging or capturing user generated content from the internet and aligning this with archived items. In this talk, the area of tension between the current state of technology and user needs is discussed in more detail in the context of practical use cases within the Netherlands Institute for Sound and Vision.
  2. Let me first introduce Sound and Vision. Sound and Vision maintains and provides access to 70 per cent of the Dutch audio-visual heritage comprising approximately 700,000 hours of television, radio, music and film, making SV one of the largest audiovisual archives in Europe. The archive is growing. SV is the business archive of the national broadcasting corporationsand digitally born television and radio made by the Dutch public broadcastering companies is flowing in right after it is broadcast. Also, via the SV archive service PROARCHIVE content from Dutch cultural heritage institutes and regional broadcast institutes flows in. Finally we are currently selecting manually Dutch user generated content from the internet. More on this later.
  3. € 173 mln in 7 jaar (looptijd 2007-2014)wel terugverdienverplichting. Tijdens looptijd € 19 mln
  4. Om dit soort use cases mogelijk te maken is handmatig beschrijven van materiaal niet de oplossing want te kostbaar en per definitie beperkt. Bij contentbeheerders ontbreken vaak de resources om zelfs minimale beschrijvingen zoals titel en datum te produceren
  5. Om materiaal toch, en in meer detail te kunnen beschrijven zijn een aantal strategieen denkbaar.Zo wordt de hulp van het publiek ingeroepen om materiaal te beschrijven, het zogenaamde crowdsourcing.Een belangrijk alternatief waar we in Twente onderzoek naar gedaan hebben is het gebruik van beschikbare tekstuele bronnen zoals ondertitels, notulen of aantekeningen, als beschrijvingen van content. Met behulp van spraaktechnologie kunnen deze beschrijvingen soms ook worden gesynchroniseerd met het materiaal (denk hierbij aan notulen) of is er al een vorm van synchronisatie aanwezig (in het geval van ondertitels. Maar vaak zijn dit soort bronnen niet beschikbaar. Dan kan technologie die op basis van audiovisuele kenmerken automatisch beschrijvingen genereert uitkomst bieden.
  6. allemaal potentieel interessante content voor verschillende typen gebruikers:producers die uit zijn op hergebruik, journalisten, onderzoekers, en natuurlijk ook het algemeen publiek.Zomaar een greep uit mogelijke use cases waar je aan kunt denken: