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Conference Paper Pre-echo reduction in transform audio coding via temporal envelope control with machine learning based estimation
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Authors
Jae-Won Kim, Byeongho Jo, Seungkwon Beack, Hochong Park
Issue Date
2024-04
Citation
International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024, pp.1-5
Publisher
IEEE
Language
English
Type
Conference Paper
Abstract
This paper proposes a new method for pre-echo reduction in transform-based audio coding by controlling the temporal envelope of the waveform. The proposed method comprises two operating modes: temporal envelope flattening and temporal envelope correction of a target signal. The proposed method estimates signal levels with a low temporal resolution from side information using machine learning and converts them into a signal to be applied to the target signal to flatten and correct the temporal envelope. It also adjusts the signals to maintain signal continuity between the non-transient and transient frames. The proposed method differs from conventional methods in that it directly modifies the waveform before encoding and after decoding, which makes it useful as a new coding tool for legacy codecs. A subjective performance evaluation confirms that the proposed method uses fewer bits to provide sound quality equivalent to that of the shortwindow transform.
KSP Keywords
Audio coding, Conventional methods, Machine learning based, Operating mode, Performance evaluation, Pre-echo, Temporal resolution, new method, side information, sound quality