Multi-Track Audio Analysis via Composite File Merging
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Solution Overview
Problem
Existing music production technologies face challenges in processing and managing multi-track recordings, particularly in detecting and editing audio characteristics such as tempo, downbeat, and signature across multiple audio tracks recorded simultaneously by different band members.
Innovation Solution
A system and method for combining multiple audio tracks into a single audio file, extracting and associating audio file characteristics, and updating metadata based on user-edited characteristics, allowing for real-time detection and editing of tempo, downbeat, and signature, while enabling exclusion of certain tracks from the combined analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple audio tracks are processed individually, then each track can be managed independently, but the analysis and editing of audio characteristics becomes time-consuming and inefficient
Solution Approach 1:
The patent combines multiple audio tracks into a single composite audio file for analysis purposes. The system extracts audio characteristics (tempo, downbeat, signature) from the combined file and then distributes these characteristics back to individual tracks, enabling efficient batch processing while maintaining track independence.
Solution Approach 2:
The system performs multiple functions using a unified approach: it analyzes all selected tracks simultaneously to detect audio characteristics, updates metadata for all tracks, and applies edits across the entire multi-track set. This multi-functional processing eliminates the need for separate analysis of each track.
2Measurement precision
If audio characteristics are extracted from each track separately, then accurate per-track analysis is achieved, but the processing time and computational resources increase significantly
Solution Approach 1:
The system merges multiple audio tracks into a single composite file for the actual audio analysis operation. By detecting tempo, downbeat, and signature from the combined audio data, the system achieves accurate characteristic extraction while processing all tracks simultaneously, thereby reducing total processing time.
Solution Approach 2:
The system performs preliminary combining of tracks before analysis, creating a unified audio file that contains the composite signal. This preliminary action allows the analysis engine to work with a single file rather than multiple files, significantly reducing processing time while maintaining accuracy.
3Productivity
If all tracks are combined into a single audio file, then audio characteristics can be detected efficiently, but certain tracks may need to be excluded from the analysis
Solution Approach 1:
The system dynamically adjusts the set of tracks to be combined based on user selection. Users can select which tracks to include or exclude from the composite file through the graphical interface. The system then processes only the selected tracks, providing flexible adaptability while maintaining batch processing efficiency for the chosen subset.
Solution Approach 2:
The system segments the multi-track set into selected and excluded portions. Only the selected tracks are combined into the composite audio file for analysis, while excluded tracks are omitted from the combining process. This segmentation allows flexible track selection while maintaining efficient processing of the relevant subset.
4Manufacturing precision
If audio characteristics are updated for one track, then precise editing is achieved, but the same edits need to be manually applied to other tracks
Solution Approach 1:
The system implements universal edit propagation across all selected tracks. When a user edits an audio characteristic (such as tempo or downbeat) for any track in the selected set, the system automatically applies the same edit to all other selected tracks. This multi-functional update mechanism maintains edit precision while eliminating repetitive manual operations.
Solution Approach 2:
The system provides feedback by detecting when an edit is made to any track and automatically propagating that edit across the entire selected track set. This feedback mechanism ensures consistency across all tracks without requiring manual intervention for each individual track, thereby improving ease of operation while maintaining precision.
Data Source
AI summary
Techniques are provided for implementing multi-track audio analysis. In some instances, a plurality of audio tracks are received and combined into a single audio file. A collection of audio file characteristics are extracted from the single audio file. In some examples, the collection of audio file characteristics are associated with of the plurality of audio tracks and the single audio file. Audio characteristic edits are received for revising the collection of audio file characteristics. Metadata associated with each of the plurality of audio tracks and for the single audio file are updated based at least in part on the audio characteristic edits.