Project Details

Description

Productivity and well-being depends on digital media and the delivery of multimodal media information on many different platforms including TV, social, and mobile media. Traditional business models in the music, audio and broadcast sectors are challenged; however, the ubiquitous digitalization of media, localization information, and human behaviors has a huge and disruptive potential to be explored in strategic research. Audio information represents a separate challenge over other modalities (e.g. text or visual information) since it can be sensed and perceived as an abstract, emotional stream. Despite the fact that higher cognitive representations of audio are well-developed, they are not easily articulated or shared by nonexperts. This project focuses on methods and tools for an augmented audio experience and making the information actionable, i.e., enable users to interpret, organize, analyze, share, cocreate, and facilitate story-telling and audio management. The strong Danish position within sound technology together with the innovative approaches of this project will help unlock the potential. We propose a multi-disciplinary strategic research project lead by DTU including Danish research institutions, commercial partners, and end-users, as well as three major English university partners. The vision is to develop a flexible modular audio data processing platform for new products and services in the commercial sector; the public service sector; and in educational and cultural research. We will prototype and evaluate solutions in all these areas. The research will combine bottom-up representation of audio and other relevant information sources with top-down user-driven feedback.
StatusFinished
Effective start/end date01/01/201231/12/2015

Activities

  • 5 Talks and presentations in private or public companies
  • 1 Conference organisation or participation
  • 1 Visiting another research institution

KTH School of Electrical Engineering

Bob L. Sturm (Visiting researcher)

3 Dec 20127 Dec 2012

Activity: Visiting another research institution

Music genre for humans and machines alike

Bob L. Sturm (Lecturer)

29 Oct 2012

Activity: Talks and presentationsTalks and presentations in private or public companies

Three experiments in music genre recognition

Bob L. Sturm (Speaker)

14 Sep 2012

Activity: Talks and presentationsTalks and presentations in private or public companies

Research Output

  • 4 Article in proceeding
  • 4 Conference article in Journal
  • 2 Journal article
  • 1 Conference abstract for conference

Are deep neural networks really learning relevant features?

Kereliuk, C., Sturm, B. L. & Larsen, J., 2015.

Research output: Contribution to conference without publisher/journalConference abstract for conferenceResearchpeer-review

  • A Closer Look at Deep Learning Neural Networks with Low-level Spectral Periodicity Features

    Sturm, B. L., Kereliuk, C. & Pikrakis, A., 2014, Proceedings of 4th International Workshop on Cognitive Information Processing (CIP 2014). Hansen, L. K., Holdt Jensen, S. & Larsen, J. (eds.). IEEE, Vol. 1. p. 1-6 6 p.

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

  • 8 Citations (Scopus)

    Classification Accuracy Is Not Enough: On the Evaluation of Music Genre Recognition Systems

    Sturm, B. L., 2013, In : Journal of Intelligent Information Systems. 41, 3, p. 371-406 36 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

    File
  • 60 Citations (Scopus)
    1164 Downloads (Pure)