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Efficient content classification and loudness estimation

A loudness, payload technology, used in speech analysis, instrumentation, etc., to solve problems such as imperfection, misclassification that affects loudness calculations, and no additional processing work expected

Inactive Publication Date: 2014-02-12
DOLBY INT AB
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this causes undesired additional processing work
Furthermore, the classification methods used to divide audio signals into different classes for the purpose of gating loudness calculations are often imperfect, thus leading to misclassifications that affect loudness calculations

Method used

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  • Efficient content classification and loudness estimation
  • Efficient content classification and loudness estimation
  • Efficient content classification and loudness estimation

Examples

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Embodiment approach

[0166] According to one embodiment, the scale factor band energy is used instead of the spectral power density used to calculate the average spectral slope described above. An example table of MDCT index 0 sets (Nm) for a sampling rate of 48kHz is shown in the table below. The scaling factor band energy is calculated as follows:

[0167] Z m = Σ n = N m N m + 1 - 1 | x n 2 | for 0 m ≤ 46

[0168] Z m = scale factor band (sfb) energy of index m

[0169] x n = MDCT coefficient of index n, 0

[0170] N m = MDCT index offset of sf...

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Abstract

The present document relates to methods and systems for encoding an audio signal. The method comprises determining a spectral representation of the audio signal. The determining a spectral representation step may comprise determining modified discrete cosine transform, MDCT, coefficients, or a Quadrature Mirror Filter, QMF, filter bank representation of the audio signal. The method further comprises encoding the audio signal using the determined spectral representation; and classifying parts of the audio signal to be speech or non-speech based on the determined spectral representation. Finally, a loudness measure for the audio signal based on the speech parts is determined.

Description

technical field [0001] This paper relates to methods and systems for active content classification and loudness estimation of audio signals. In particular, it relates to active content classification and gated loudness estimation within audio encoders. Background technique [0002] Portable handheld devices such as PDAs, smartphones, mobile phones, and portable media players often include audio and / or video rendering capabilities and have become important entertainment platforms. The continued penetration of wireless or wired transmission capabilities into such devices drives their development forward. Thanks to the support of media transmission and / or storage protocols such as the High Efficiency Advanced Audio Coding (HE-AAC) format, media content can be continuously downloaded and stored to portable handheld devices, providing a practically unlimited amount of media content . [0003] HE-AAC is a lossy data compression scheme for digital audio defined as the MPEG-4 aud...

Claims

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Application Information

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IPC IPC(8): G10L19/16G10L19/24G10L25/78
CPCG10L2025/783G10L19/167G10L19/24G10L25/93
Inventor 哈拉尔德·蒙特阿里希特·比斯瓦斯罗尔夫·迈斯纳
Owner DOLBY INT AB
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