Audio Signal Blending With ML Quality Scoring for Smooth FM Switching
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Solution Overview
Problem
Conventional FM radio receivers switch between FM signals based on power levels, leading to deteriorated audio quality and interruptions before the power level drops below the threshold, affecting the listening experience.
Innovation Solution
A system using a digital signal processing (DSP) circuit with a trained machine learning model to analyze audio quality scores, blending audio signals based on quality rather than power levels, ensuring smoother transitions and improved listening experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the primary FM signal is selected as the output signal based on power strength comparison, then the signal strength is maintained above acceptable levels, but the audio quality deteriorates due to late switching decision
Solution Approach 1:
The system performs preliminary analysis of audio quality parameters (signal-to-noise ratio, distortion levels, fading characteristics) before the power strength drops below the threshold. This early detection enables proactive switching to the alternative FM signal, preventing audio quality deterioration while maintaining reliable signal strength.
Solution Approach 2:
The system continuously monitors multiple parameters including power strength, audio quality metrics, and signal characteristics of both primary and alternative FM signals. This feedback mechanism allows dynamic adjustment of switching decisions based on real-time signal conditions, resolving the contradiction between maintaining strength and preventing quality deterioration.
2Ease of operation
If switching is based solely on power level threshold, then the switching decision is simple and fast, but multiple interruptions occur due to deteriorated audio quality before threshold breach
Solution Approach 1:
The system evaluates audio quality parameters in advance before the power threshold is breached. By assessing signal-to-noise ratio, distortion, and fading patterns early, the system makes informed switching decisions that prevent interruptions, maintaining playback continuity without sacrificing operational simplicity.
Solution Approach 2:
The system transitions from relying on a single power level parameter to monitoring multiple parameters simultaneously (power strength, audio quality metrics, signal characteristics). This multi-parameter approach improves reliability while maintaining ease of operation through automated composite evaluation.
3Object-affected harmful factors
If the alternative FM signal is selected earlier to prevent audio quality deterioration, then the listening experience is improved, but the power strength of the primary signal may still be above acceptable levels causing unnecessary switching
Solution Approach 1:
The system uses continuous feedback from multiple signal parameters to determine the optimal switching moment. By analyzing the trend of audio quality degradation alongside power strength levels, the system switches only when necessary, preventing both quality deterioration and unnecessary switching that would waste energy.
Solution Approach 2:
The system dynamically adjusts switching decisions based on the combined evaluation of power strength and audio quality parameters. This adaptive approach ensures switching occurs at the precise moment when it becomes necessary, balancing audio quality maintenance with energy efficiency by avoiding premature or unnecessary switches.
Data Source
AI summary
A digital signal processing (DSP) circuit of a system for blending audio signals executes a trained machine learning model to extract audio parameters associated with audio blocks of two received audio signals and generates audio quality scores. Each audio quality score indicates an audio quality of the audio block. Upon analyzing the corresponding audio quality scores of the two audio signals, the DSP circuit outputs an audio block of one of the audio signals based on a previous blended block or blends one of the audio blocks of the two audio signals to output a blended block that includes a composition of the corresponding audio blocks of the two audio signals. The system thus outputs an audio output signal that includes such audio blocks that are associated with at least one of the two audio signals.