Dialogue Equalization Switching for Clearer Speech Playback
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Solution Overview
Problem
In home theaters and audio systems, speech or dialogue in audio signals often becomes less intelligible due to varying surround sound configurations and recording profiles, making it difficult for users to enhance sound components effectively without manual adjustments, which can be inconvenient and lead to suboptimal sound quality.
Innovation Solution
A method and apparatus using a trained machine-learning network to detect speech components in audio signals, transitioning from an original equalization mode to a speech equalization mode that enhances linguistic meanings, by analyzing energy levels and categorizing audio content into speech, music, and singing components, and applying dynamic equalization settings to improve intelligibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual equalization adjustments are made to enhance speech components, then speech intelligibility is improved, but user convenience deteriorates and operation complexity increases
Solution Approach 1:
The system automatically detects speech components in audio signals and applies appropriate equalization settings without requiring manual user intervention. The machine learning model continuously monitors audio content and dynamically adjusts equalization parameters to enhance speech intelligibility autonomously
Solution Approach 2:
The system performs preliminary detection and classification of audio content before applying equalization. By analyzing audio signals in advance and identifying speech components, the system prepares optimal equalization settings proactively, ensuring speech enhancement is applied at the right moments without user input
2Measurement precision
If speech equalization mode is applied continuously, then speech intelligibility is improved, but audio quality for non-speech content deteriorates
Solution Approach 1:
The system dynamically switches between different equalization modes based on real-time audio content analysis. The machine learning model continuously classifies audio segments as speech, music, or other content types, and adjusts equalization settings accordingly, applying speech enhancement only when speech components are detected
Solution Approach 2:
The system applies different equalization characteristics to different portions of the audio signal based on content type. Speech components receive enhanced equalization settings for improved intelligibility, while music and other non-speech content maintain their original or optimized settings, ensuring each content type receives appropriate processing
3Ease of operation
If automatic speech detection is implemented, then user convenience is improved, but device complexity increases
Solution Approach 1:
The system introduces a machine learning model as an intermediary component that automatically analyzes audio signals and controls equalization settings. This intelligent mediator detects speech components, classifies audio content, and manages mode transitions, providing automatic speech enhancement while maintaining ease of use despite the added computational complexity
Data Source
AI summary
Processes, methods, systems, and devices are disclosed for intelligently detecting speech or in audio signals and smoothly transitioning to mode that enables a user to better understand the speech. For example, aspects of the present disclosure provide method for processing and producing audio signals. During playback of an audio signal, the method analyzes content of the audio signal prior to the playback of the content to determine whether one or more predefined conditions are met to indicate that the content includes speech. In response to determining the one or more predefined conditions are met, the method automatically applies to the audio signal a first playback equalization configured to enhance the speech within the content. In response to determining the one or more predefined conditions are not met, the method comprises applying to the audio signal no playback equalization or a second playback equalization different from the first playback equalization.