Broadcast Audio Quality Improvement via Multi-Recording Alignment
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Solution Overview
Problem
Current methods for recording broadcast audio are inefficient, as listeners often miss desired programs due to lack of timely recording activation, difficulty in identifying programs, and poor quality recordings plagued by errors such as noise and interference, with no standard method for rating recording quality.
Innovation Solution
A method and apparatus for automatically recording and improving broadcast audio by aligning multiple recordings, identifying program boundaries, and generating a higher-quality recording through sample comparison and error correction, while providing an audio program guide for identification and quality rating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple recordings are made and compared to improve quality, then recording quality is improved, but device complexity and processing time increase
Solution Approach 1:
The system divides the audio recording process into multiple independent recording instances, each capturing the same broadcast program separately. These segmented recordings are then processed individually through alignment and sampling operations before being combined, allowing quality improvement while maintaining manageable processing complexity through modular operations.
Solution Approach 2:
The system creates multiple copies of the same audio program through separate recording instances. These copies are then compared and sampled to generate a final high-quality recording. The copying approach enables quality verification and error correction while the standardized sampling process keeps processing complexity controlled.
2Manufacturing precision
If multiple recordings are made and compared to improve quality, then recording quality is improved, but processing time increases
Solution Approach 1:
The system performs preliminary alignment of multiple recordings to a common time reference before the actual comparison and sampling process. This preliminary action establishes proper temporal relationships between recordings, enabling efficient subsequent processing and reducing overall processing time while maintaining quality improvement benefits.
Solution Approach 2:
The system samples only specific portions of the multiple recordings at strategically selected time points rather than processing entire recordings. This partial action approach achieves quality verification and error correction with significantly reduced processing time compared to analyzing complete recordings.
3Productivity
If automated recording is implemented, then productivity is improved, but difficulty in identifying and measuring program boundaries increases
Solution Approach 1:
The system uses feedback from analyzing multiple recordings to automatically identify program boundaries. By comparing temporal patterns and content similarities across multiple recordings, the system refines its detection of program start and end points, improving boundary detection accuracy while maintaining automated recording efficiency.
Solution Approach 2:
The system transitions from analyzing a single recording dimension to comparing multiple recording dimensions simultaneously. This multi-dimensional approach provides additional temporal and content-based cues for identifying program boundaries, making automated detection more accurate despite the increased complexity of managing multiple recordings.
Data Source
AI summary
Recordings of broadcast audio content often contain errors (e.g., noise, signal loss, interference, talkover). A method and apparatus are provided for improving the quality of such a recording. Multiple recordings of a broadcast audio program are identified, and are aligned according to some time index of the program, such as the beginning, midpoint or end of one of the recordings. Samples of each recording are taken and compared. If a majority (or plurality) of the samples agree (e.g., they match within an allowable threshold of variance), one of them is used to generate or populate a new recording. If there is no majority (or plurality), one of the samples may be chosen at random, on the basis of which recording has most often been in the majority (or plurality), or on some other basis. Or, the method may be repeated or extended to obtain samples of other recordings.