• Corpus ID: 17213221

Computationally Created Soundscapes with Audio Metaphor

@inproceedings{Thorogood2013ComputationallyCS,
  title={Computationally Created Soundscapes with Audio Metaphor},
  author={Miles Thorogood and Philippe Pasquier},
  booktitle={ICCC},
  year={2013}
}
Soundscape composition is the creative practice of processing and combining sound recordings to evoke auditory associations and memories within a listener. [] Key Method We used a simple natural language processing to create audio file search queries, and we segmented and classified audio files based on general soundscape composition categories. We used our prototype implementation of Audio Metaphor in two performances, seeding the system with

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References

SHOWING 1-10 OF 23 REFERENCES
Audio Metaphor: Audio Information Retrieval for Soundscape Composition
TLDR
Audio Metaphor facilitated audience interaction by listening for Tweets that the audience addressed to the performance; in this case, it processed the Twitter feed in realtime to recommend audio files to the soundscape composer.
Design of a Generative Model for Soundscape Creation
TLDR
This paper describes the design and preliminary implementation, of a generative model for dynamic, real time soundscape creation and outlines extensions to the model that include interaction paradigms, context modeling, sound acquisition, and sound synthesis.
Soundscape Generation for Virtual Environments using Community-Provided Audio Databases
TLDR
The design methodology incorporates the use of concatenative synthesis to construct a sound environment using online community-provided sonic material, and an application is described in which sound environments are generated for Google Street View using the online sound database Freesound.
Negotiated Content: Generative Soundscape Composition by Autonomous Musical Agents in Coming Together: Freesound
TLDR
This work presents a system – Coming Together: Freesound – in which four autonomous artificial agents choose sounds from a large pre-analyzed database of soundscape recordings (from freesound.org), based upon their spectral content and metadata tags.
Authoring augmented soundscapes with user-contributed content
TLDR
A complete augmented soundscapes system that, in an autonomous and continuous manner, spatializes virtual acoustic sources in a geographic location and combines the traditional text-query with content-based audio classification.
Sonic Experience: A Guide to Everyday Sounds
Le repertoire des effets sonores en anglais. Never before has the everyday soundtrack of urban space been so cacophonous. Since the 1970s, sound researchers have attempted to classify noise, music,
Understanding urban and natural soundscapes
The concept of soundscape has garnered increasing research attention over the last decade for studying and designing the sonic environment of public spaces. It is therefore critical to advance
In search for soundscape indicators : Physical descriptions of semantic categories
We present converging evidence that people categorize urban soundscapes into semantic categories related to social activities. Examples of such categories are spontaneously described are « markets»,
Freesound 2: An Improved Platform for Sharing Audio Clips
Freesound.org is an online collaborative sound database where people from different disciplines share recorded sound clips under Creative Commons licenses. It was started in 2005 and it is being
Automatic audio segmentation using a measure of audio novelty
  • J. Foote
  • Computer Science
    2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532)
  • 2000
TLDR
This method can find individual note boundaries or even natural segment boundaries such as verse/chorus or speech/music transitions, even in the absence of cues such as silence, by analyzing local self-similarity.
...
1
2
3
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