Automated Sound Effect Placement via Onset Strength Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current audio mixing processes rely heavily on manual experimentation and trial-and-error for placing sound effects in music, which can be time-consuming and inaccessible to those without experience.
Innovation Solution
An automated method for selecting sound effect placement points in a music audio signal using onset strength analysis, boosting, and mel-spectrogram or constant-Q transform criteria, allowing for the systematic insertion of sound effects into music audio signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual experimentation and trial-and-error methods are used for placing sound effects, then the mixing process allows for creative exploration, but the process becomes time-consuming and inaccessible to inexperienced users
Solution Approach 1:
The system performs automatic sound effect placement by analyzing the music audio signal itself to identify suitable insertion points based on onset strength, allowing the signal to select its own optimal placement locations without requiring manual user intervention or expertise
Solution Approach 2:
The manual mechanical process of trial-and-error mixing is replaced with an automated computational system that uses signal processing algorithms to objectively determine sound effect placement points based on acoustic features like onset strength
2Extent of automation
If automated methods are used to determine sound effect placement points, then the mixing process becomes accessible to inexperienced users, but the system complexity increases
Solution Approach 1:
The system extracts only the essential feature (onset strength) from the complex music audio signal to determine placement points, isolating the critical information needed for automated decision-making while ignoring other complex aspects of the audio signal
Solution Approach 2:
The system transforms the complex audio signal into a simplified parameter representation (onset strength time series) that captures the essential temporal structure needed for placement decisions, changing the parameter space from raw audio waves to meaningful acoustic features
3Measurement precision
If sound effects are placed at points with highest onset strength only, then the placement is objectively determined, but important rhythmic patterns may be missed
Solution Approach 1:
The system merges multiple criteria (onset strength detection and rhythmic pattern recognition) into a unified placement decision process, combining the objective temporal information from onset strength with the musical structure information from rhythmic patterns to select final placement points
Data Source
Figure 1
Figure 2
Figure 2
AI summary
A method of selecting points in a music audio signal for placement of a sound effect comprises searching for points in the music audio signal as potential candidate placement points based on one or more criteria such as melspec or CQT. An onset strength time series for the music audio signal is determined and boosted at points found by the search. Points are then selected from the boosted onset strength time series with a value larger than a predetermined threshold as candidate points for the placement of the sound effect.