Audio Metaphor is a research project aimed toward the design of new methodologies and tools for sound design and composition practices in the areas of film sound, game sound, and sound art. We continue to identify the processes involved with working with audio recordings in creative environments, and address these in our research by implementing computational systems to assist human operations. We have successfully developed Audio Metaphor for retrieval of audio file recommendations from natural language texts, and, even used phrases automatically generated from Twitter to sonify the current state of the Web2.0. Another success has been in the segmentation and classification of environmental audio with composition specific categories, which was then used to in a generative systems approach allowing users to generate sound design by simply entering text. As we point Audio Metaphor toward perception and cognition, we will continue to contribute to the music information retrieval field through environmental audio classification and segmentation, and moreover, be instrumental in the design and implementation of the new tools for sound designers and artists.
Papers & Posters:
- Thorogood, M, Pasquier, P., and Eigenfeldt, A. (2012). “Audio Metaphor: Audio Information Retrieval for Soundscape Composition” Sound and Music Computing (SMC). Copenhagen, Denmark, PDF
- Thorogood, M., Pasquier, P. (2013). “Computationally Generated Soundscapes with Audio Metaphor” In Proceedings of the 4th International Conference on Computational Creativity (ICCC). Sydney, Australia,
- Thorogood, M., Pasquier, P. (2013). “Impress: A Machine Learning Approach to Soundscape Affect Classification for a Music Performance Environment” Proceedings of the 13th International Conference on New Interfaces for Musical Expression (NIME). Daejeon + Seoul, Korea Republic .