Cue Point Generation Using Beat Grid Scoring
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Solution Overview
Problem
Generating accurate and musically correct cue points in musical pieces is challenging due to the complexity and variation of different musical genres, making it difficult to identify specific markers like the start of vocals, melodies, or transitions within songs.
Innovation Solution
An apparatus and method that generate cue points by creating a beat grid, calculating scores based on audio features like transient energy and melodic energy, and determining cue points at specific positions using these scores, with the ability to filter and weight features for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to generate cue points, then flexibility in identifying specific markers is maintained, but accuracy and consistency deteriorate due to complexity and variation of different musical genres
Solution Approach 1:
The system segments the musical piece into a beat grid structure, dividing the continuous audio signal into discrete beat positions and temporal divisions. This segmentation allows for systematic analysis of audio features at specific rhythmic intervals, improving cue point accuracy by evaluating transitions at structurally significant positions rather than treating the entire piece as a continuous signal.
Solution Approach 2:
The system changes parameters by calculating multiple audio features (transient energy, melodic energy, spectral characteristics) at each beat grid position and comparing them across different time points. By analyzing parameter changes and transitions in these features, the system identifies musically significant moments with high accuracy across diverse genres without requiring manual intervention.
2Productivity
If automated cue point generation is implemented, then productivity and consistency improve, but difficulty in detecting and measuring musically correct positions increases due to genre variation
Solution Approach 1:
The system performs preliminary action by first generating a beat grid and calculating audio feature values for all beat positions before identifying cue points. This preliminary analysis of the entire musical structure enables the system to quickly and consistently detect musically correct positions by comparing pre-computed features against transition criteria, improving both productivity and accuracy across different genres.
Solution Approach 2:
The system uses feedback by calculating scores based on comparisons of audio feature values before and after potential cue point positions. The scoring mechanism provides feedback on how well each position meets the criteria for a musically significant transition, allowing the system to automatically identify correct positions with high consistency while maintaining the ability to adapt to genre-specific characteristics.
Data Source
AI summary
An apparatus, method, and computer-readable storage medium that generate at least a cue point in a musical piece. The method includes generating a beat grid representing the musical piece, determining values for the beat grid, the values corresponding to an audio feature of the musical piece, and each value representing an entire duration of each beat in the beat grid of the musical piece, calculating a score for the audio feature at each of a plurality of positions in the beat grid of the musical piece, using some or all of the determined values, and generating the cue point at a particular position of the plurality of positions, based on the calculated scores.