Acoustic Environment Data Reuse via Centralized Repository
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Solution Overview
Problem
Existing audio signal processing techniques are computationally and time-intensive for estimating acoustic environment characteristics like reverberation, making them impractical for real-time applications.
Innovation Solution
A system comprising an acoustic environment server and audio devices that upload and download acoustic environment data, allowing devices to leverage pre-measured data, reducing the need for repeated calculations and storage of reverberation, echo, and noise levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic environment characteristics are estimated using traditional signal processing techniques, then measurement precision is improved, but computational complexity and time consumption increase significantly
Solution Approach 1:
The system performs acoustic environment measurements in advance and stores the results in a database. When a device needs acoustic environment data, it queries the database for pre-computed results matching its location, avoiding the need to perform complex calculations in real-time. This preliminary action resolves the contradiction by preparing accurate measurements beforehand, making them readily available without computational overhead during actual use.
Solution Approach 2:
The system creates copies of acoustic environment data measured at one location and stores them in the database for reuse by other devices at the same or similar locations. Instead of each device independently performing complex measurements, they can copy and use previously measured data from the database, maintaining measurement precision while dramatically reducing computational complexity.
2Measurement precision
If acoustic environment data is measured and stored for each location, then measurement precision is improved, but loss of time increases due to repeated measurements
Solution Approach 1:
Acoustic environment measurements are performed in advance and stored in the database before they are needed. This preliminary action ensures that accurate measurements are already available when devices query the database, eliminating the time loss associated with performing measurements at the moment they are needed.
Solution Approach 2:
The system recovers and reuses acoustic environment data from the database instead of discarding previously measured data. By querying the database for existing measurements and reusing them, the system avoids the time-consuming process of repeated measurements while maintaining data accuracy through selective recovery of relevant historical data.
3Reliability
If acoustic environment data is stored locally on each device, then reliability is improved, but device complexity and storage requirements increase
Solution Approach 1:
The system merges the storage function into a centralized database rather than requiring each device to maintain its own complete dataset. Devices query the centralized database for needed acoustic environment data, combining the benefits of centralized storage efficiency with reliable data access. This resolves the contradiction by providing data availability through the database while reducing individual device complexity and storage requirements.
Solution Approach 2:
The centralized database acts as an intermediary between devices and acoustic environment data. Instead of devices directly storing and managing all acoustic data, the database mediates by storing, organizing, and providing data to devices on demand. This intermediary approach maintains reliability of data access while reducing the storage and processing burden on individual devices.
Data Source
AI summary
Systems and methods are described for storing and reusing previously generated/calculated acoustic environment data. By reusing acoustic environment data, the systems and methods described herein may avoid the increased overhead in generating/calculating acoustic environment data for a location when this data has already been generated and is likely accurate. In particular, the time and complexity involved in determining reverberation/echo levels, noise levels, and noise types may be avoided when this information is available in storage. This previously stored acoustic environment data may not be limited to data generated/calculated by the same audio device. Instead, in some embodiments an audio device may access a centralized repository to leverage acoustic environment data generated/calculated by other audio devices.