Set-Top Box Audio Parameterization by Stream Genre Detection
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Solution Overview
Problem
Existing audio playback systems in set-top boxes require manual user intervention for sound output adjustments, which is restrictive and unreliable, deterring non-experienced users and failing to optimally adapt to broadcast content.
Innovation Solution
A decoder box with a processing unit that performs real-time multimodal analysis of audio and video data sources to automatically adapt audio playback settings based on the genre of the input stream, using classification models like transformers and convolutional neural networks to optimize sound rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual user intervention is used for audio playback adjustments, then users can control sound output settings, but the system becomes restrictive and unreliable for non-experienced users
Solution Approach 1:
The system automatically analyzes the input stream metadata to determine content genre and adjusts audio parameters without user intervention. The configuration module performs real-time analysis and self-configures the audio playback device based on detected content type, making the system serve itself rather than requiring manual user control.
Solution Approach 2:
The system dynamically changes audio parameters (such as equalization settings, volume levels, and sound profile) based on the detected genre of the input stream. Different parameter sets are applied automatically for different content types like music, speech, or cinematic content, optimizing sound output for each genre without manual adjustment.
2Adaptability or versatility
If manual audio mode selection is implemented, then audio playback can be adapted to content type, but the system fails to reliably identify suitable modes for all broadcast streams
Solution Approach 1:
The system continuously analyzes the input stream metadata and uses the results to automatically select and switch between different audio modes. The configuration module monitors the broadcast content in real-time and provides feedback-driven adjustments, ensuring the audio playback device operates in the most appropriate mode for the current content being played.
Solution Approach 2:
The system replaces manual mechanical selection (physical buttons or menu navigation) with automated electronic analysis and control. Machine learning models and metadata processing algorithms automatically identify content genre and trigger appropriate audio mode changes, substituting human intervention with intelligent automated systems that reliably interpret broadcast content.
3Productivity
If automated genre detection is implemented, then audio output can be quickly adapted to broadcast content, but the system complexity increases with multiple analysis modules
Solution Approach 1:
The automated analysis system is divided into distinct functional modules: metadata extraction module, genre classification module, and audio parameter configuration module. Each module performs a specific task in the analysis chain, allowing the system to process content type identification efficiently through specialized sub-components rather than a monolithic complex structure.
Data Source
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AI summary
Decoder box (1), comprising: - a parameterization module (11) arranged to: o perform and/or control in real time analyses on at least two distinct data sources relating to the input stream (F), the data sources being chosen from metadata associated with the input stream, a current audio signal from the input audio signal, and, if the input stream also includes an input video signal, at least one target image from the input video signal; o define, from the results of these analyses, a genre of the input stream (F), the genre being associated with audio parameters; - a configuration module (10) which dynamically adapts, using the audio parameters, a setting of an audio playback device integrated in or connected to the decoder box (1) and comprising at least one speaker (4).