Presentation Loudness Metadata for Consistent Audio Substream Mixing
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Solution Overview
Problem
Existing audio encoding and decoding technologies struggle to maintain accurate loudness consistency across different audio content substreams, leading to potential inaccuracies that exceed industry tolerances, such as 0.1 dB, when switching languages or adding commentary tracks.
Innovation Solution
The proposed solution involves providing loudness data for each presentation data structure, which includes mixing coefficients and dynamic range compression (DRC) data, allowing decoders to adjust and combine substreams to achieve a desired loudness level accurately, ensuring consistency across different presentations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple content substreams are mixed to create different presentations, then content flexibility and adaptability are improved, but loudness consistency deteriorates
Solution Approach 1:
The encoder pre-calculates and embeds loudness data for multiple possible presentations (different language combinations, commentary tracks, etc.) in the bitstream. This preliminary action allows the decoder to directly retrieve and apply the correct loudness compensation without real-time calculation, ensuring consistent loudness across different content mixings while maintaining full adaptability.
Solution Approach 2:
Loudness data acts as an intermediary between the encoded content substreams and the final output loudness. The decoder uses this intermediate loudness information to adjust and compensate the mixed substreams, ensuring that regardless of which combination of substreams is selected, the final loudness remains consistent within tight tolerances.
2Measurement precision
If loudness data is provided for each presentation data structure, then loudness measurement precision is improved, but device complexity increases
Solution Approach 1:
Instead of implementing complex real-time loudness measurement and calculation algorithms in the decoder, the patent copies pre-calculated loudness data from the encoder into the bitstream. The decoder simply retrieves and applies this copied data, achieving high measurement precision while keeping the decoder complexity low.
3Manufacturing precision
If tight loudness tolerances (0.1 dB) are enforced across all presentations, then loudness consistency is improved, but processing complexity increases
Solution Approach 1:
The encoder performs the complex processing of calculating loudness data for multiple presentations in advance and embeds these results in the bitstream. This shifts the processing complexity from the decoder to the encoder, allowing the decoder to achieve tight loudness tolerances (0.1 dB) through simple retrieval and application of pre-computed values rather than complex real-time processing.
Data Source
AI summary
This disclosure falls into the field of audio coding, in particular it is related to the field of providing a framework for providing loudness consistency among differing audio output signals. In particular, the disclosure relates to methods, computer program products and apparatus for encoding and decoding of audio data bitstreams in order to attain a desired loudness level of an output audio signal.