Audio Metadata Stream Structure Determination
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Solution Overview
Problem
The analysis of audio metadata streams is challenging due to their unstructured nature and varying quality, lacking standard conventions, which hinders sophisticated analysis and effective processing.
Innovation Solution
An apparatus and method that processes audio metadata streams by extracting metadata elements, searching a database for matching results, computing combination scores, and determining the structure of metadata entries, allowing for the identification of relevant information such as currently playing content, and integrating with machine learning techniques for enhanced analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If automated analysis of audio metadata streams is performed, then information about currently playing content can be obtained, but the analysis is challenging due to the unstructured nature and varying quality of metadata streams
Solution Approach 1:
The patent transforms unstructured metadata streams into structured data by changing the organizational parameters of the metadata. It extracts metadata elements and organizes them according to a defined structure schema, converting variable-quality unstructured input into standardized structured output that can be reliably analyzed.
Solution Approach 2:
The patent introduces an intermediary processing layer that includes a structure determination module and a matching module. This intermediary transforms the raw unstructured metadata into a standardized format by determining its structure and matching it against known metadata schemas, thereby bridging the gap between unstructured input and structured analysis requirements.
2Measurement precision
If sophisticated analysis of audio metadata streams is performed, then better quality analysis results can be achieved, but the unstructured nature and lack of conventions make the analysis challenging
Solution Approach 1:
The patent segments the complex analysis task into distinct functional modules: a structure determination module that identifies metadata structure, a matching module that compares metadata against schemas, and an extraction module that retrieves specific information. This segmentation reduces complexity by breaking down the sophisticated analysis into manageable, specialized components.
Solution Approach 2:
The patent performs preliminary actions by establishing a structure schema and organizing metadata elements before conducting the actual analysis. It pre-defines the expected structure of metadata streams and uses this predefined framework to guide the extraction and matching processes, thereby improving analysis quality while managing complexity through preparatory organization.
3Reliability
If metadata elements are extracted and structured from audio metadata streams, then accurate analysis can be performed, but processing unstructured data with varying quality requires sophisticated processing
Solution Approach 1:
The patent implements a self-service mechanism where the structure determination module automatically analyzes the metadata stream and determines its structure without requiring manual configuration. The system adapts to different metadata formats by autonomously identifying patterns and organizing data according to appropriate schemas, thereby improving reliability while minimizing the need for complex manual processing setup.
Solution Approach 2:
The patent incorporates feedback mechanisms where the matching module compares extracted metadata against known schemas and provides feedback to the structure determination module. This feedback loop allows the system to learn from mismatches and improve its structure determination accuracy over time, enhancing reliability through iterative refinement rather than requiring perfectly complex processing systems.
Data Source
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AI summary
An apparatus, method and computer program code for processing an audio metadata stream are disclosed. The method comprises: receiving (204) a first metadata entry from an audio metadata stream associated with an audio stream; extracting (206) first metadata elements from the first metadata entry; searching (208) the database for each of the first metadata elements to receive result sets; selecting (210), from the result sets, matching result elements for the first metadata elements; mapping (212) metadata types associated with the matching result elements to positions of the first metadata elements in the first metadata entry; and determining (214) a structure of the first metadata entry based on the mapping.