Audio Processor Synchronous Asynchronous Analysis
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Solution Overview
Problem
Current audio processing systems lack efficient methods for real-time analysis and metadata generation of musical properties from audio signals, limiting musicians' ability to record, review, and manipulate their work effectively.
Innovation Solution
A system that includes an audio processor capable of synchronous and asynchronous analysis of audio data to generate transitory and aggregate musical properties, which are then stored as metadata, allowing for real-time processing and post-processing of audio files to determine chord estimates, key signatures, and chord progressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time analysis of audio data is performed to generate transitory musical properties, then processing speed and responsiveness are improved, but computational resources and processing complexity increase
Solution Approach 1:
The audio analysis process is divided into two independent segments: synchronous analysis for real-time transitory properties and asynchronous analysis for aggregate properties. This segmentation allows each segment to operate independently with appropriate computational resources, achieving real-time performance without overwhelming complexity.
Solution Approach 2:
The system dynamically adjusts processing modes based on needs - synchronous mode for real-time requirements and asynchronous mode for batch processing. This dynamic switching allows the system to optimize between speed and complexity based on the specific task requirements.
2Measurement precision
If asynchronous analysis is performed to generate aggregate musical properties, then processing accuracy and validation are improved, but processing time and latency increase
Solution Approach 1:
The system performs preliminary synchronous analysis to generate transitory properties immediately, then uses asynchronous analysis to validate and refine these properties. This preliminary action ensures that basic functionality is available quickly while accuracy is improved through subsequent validation without requiring the entire process to wait for completion.
Solution Approach 2:
The asynchronous analysis provides feedback to validate and correct transitory properties generated synchronously. This feedback mechanism allows the system to maintain high accuracy by continuously refining results without requiring the initial processing to complete entirely, thus managing time loss effectively.
3Adaptability or versatility
If multiple analysis modes (synchronous and asynchronous) are implemented, then functionality and versatility are improved, but system complexity and resource requirements increase
Solution Approach 1:
The audio processor is designed with multi-functionality to handle both synchronous and asynchronous analysis modes, as well as various audio formats and musical properties. This universal design allows a single system to serve multiple purposes - real-time processing, batch processing, validation, and metadata generation - without requiring separate specialized systems for each function.
Data Source
AI summary
A platform or system is disclosed for performing musical analysis to detect musical properties in received live or pre-recorded audio data. The analysis can include a synchronous analysis for generating estimated one or more transitory musical properties and an asynchronous analysis for generating one or more aggregate musical properties which can be applied to the transitory musical properties to generate confirmed musical properties, which can be stored as metadata associated with an audio file. In some cases, live audio data can be received, recorded, dynamically analyzed to provide realtime metadata (e.g., to a display), then the realtime metadata can be analyzed to provide confirmed, updated, or validated metadata. In some cases, initial analysis (e.g., dynamic analysis) can determine chord estimates, usable in further analysis (e.g., offline analysis) to estimate a musical key, which can then be applied to the chord estimates to determine the most likely chord estimates and determine chord progressions.