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Recent research projects have attempted to realize high realism of reproduced sound fields. We propose an innovative method, an automatic scene discrimination, for a user-centric rendering of enhanced realism in the home theater application. The method categorizes various scenes of movie contents based on their audio characteristics, and applies a pre-determined signal processing for each category in real-time. The training model was able to classified new movie contents with a 71% correct ratio. Listeners reported that this scene-based adaptive sound processing bring higher realism.
Author (s): Yuyama, Yuta; Kim, Sungyoung; Okumura, Hiraku
Affiliation:
Yamaha Corporation, Shizuoka, Japan; Rochester Institute of Technology, Rochester, NY, USA
(See document for exact affiliation information.)
Publication Date:
2018-07-06
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Session subject:
Sound Field Reproduction; Multichannel Audio; Home Theater System; Scene Classification; Machine-Learning; SVM; Feature-Extraction
Permalink: https://aes2.org/publications/elibrary-page/?id=19646
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Yuyama, Yuta; Kim, Sungyoung; Okumura, Hiraku; 2018; Movie Scene Classification Using Audio Signals in a Home-Theater System [PDF]; Yamaha Corporation, Shizuoka, Japan; Rochester Institute of Technology, Rochester, NY, USA; Paper EB1-6; Available from: https://aes2.org/publications/elibrary-page/?id=19646
Yuyama, Yuta; Kim, Sungyoung; Okumura, Hiraku; Movie Scene Classification Using Audio Signals in a Home-Theater System [PDF]; Yamaha Corporation, Shizuoka, Japan; Rochester Institute of Technology, Rochester, NY, USA; Paper EB1-6; 2018 Available: https://aes2.org/publications/elibrary-page/?id=19646