Music Rhythm Lighting Control With Noise-Filtered Beat Detection
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Solution Overview
Problem
Existing intelligent LED light strips struggle with noise interference, leading to poor correlation between audio rhythmic beats and lighting effects, especially in continuous high-volume rhythms, resulting in visually unobvious rhythmic changes.
Innovation Solution
A method involving filtering, normalizing, and windowing audio frequency signals to extract music rhythms, followed by exponential forecasting and differential equation calculations to dynamically output lighting effects that align with music rhythms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple volume-based control is used for LED lights, then the system is simple to operate, but the correlation between music rhythms and lighting effects is poor
Solution Approach 1:
The audio signal processing is segmented into multiple stages: raw audio collection, noise filtering, rhythm feature extraction, exponential smoothing forecasting, and lighting control. This segmentation allows complex rhythm detection to be broken down into manageable steps, improving precision while maintaining operational simplicity through automated processing.
Solution Approach 2:
An intermediary processing system is introduced between the audio input and LED control. This intermediary includes filtering modules, rhythm extraction algorithms, and exponential smoothing forecasting that translate raw audio into refined rhythm signals, thereby improving correlation without requiring user intervention.
2Measurement precision
If noise filtering and rhythm extraction are implemented, then the correlation between music rhythms and lighting effects is improved, but the device complexity increases
Solution Approach 1:
Complex mechanical or hardware-based noise filtering is replaced with software-based digital signal processing. The filtering, rhythm extraction, and exponential smoothing are implemented through algorithms rather than physical components, reducing device complexity while maintaining high rhythm detection precision.
Solution Approach 2:
The system performs self-service by automatically filtering noise, extracting rhythm features, and adjusting lighting parameters without user intervention. The exponential smoothing forecasting algorithm autonomously processes audio signals and generates control commands, simplifying the user interface while achieving precise rhythm-correlated lighting effects.
3Speed
If direct audio signal control is used, then the response time is fast, but the rhythmic changes are not visually obvious in continuous high-volume rhythms
Solution Approach 1:
Preliminary action is taken by pre-processing audio signals through filtering and rhythm feature extraction before controlling the LEDs. The exponential smoothing forecasting is performed in advance to predict rhythm patterns, allowing the system to prepare lighting effects that will be visually obvious before the actual music events occur, thus maintaining fast response while improving visual clarity.
Solution Approach 2:
Parameter changes are applied to the audio signal processing, specifically using exponential smoothing forecasting to transform raw audio parameters into refined rhythm parameters. This transformation enhances the visibility of rhythmic changes by adjusting the sensitivity and threshold parameters, making subtle rhythm variations detectable even in continuous high-volume music.
4Measurement precision
If exponential forecasting and differential equation calculations are performed, then the calculation accuracy is improved, but the calculation cost increases
Solution Approach 1:
Partial action is applied by performing exponential smoothing forecasting only on the most critical rhythm parameters rather than processing the entire audio signal spectrum. This selective processing maintains high prediction accuracy for the dominant rhythm features while reducing overall calculation energy consumption by focusing computational resources on the most impactful parameters.
Data Source
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AI summary
The present invention discloses a lighting effect display method and terminal based on music rhythm, by filtering the collected audio frequencies of music, and extracting music rhythms, more accurate lighting effects can be accommodated for the audio frequencies; normalizing and windowing the audio frequency signals, and converting to be acoustic pressure level data, conducting exponential forecasting and calculating variation values thereof, therefore, by treatment, converting and forecasting of the audio frequency signals, the variation values of the audio frequencies can be obtained, computational speed is improved while computational cost reduced. When the variation values reach a triggering condition, lighting effects dynamically matched with the music rhythms can be output, so as to improve correlation between the music rhythms and lighting effects, and provide good rhythmic lighting change experience.