Audio Channel Layout Detection for Accurate Multi-Track Streaming
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Solution Overview
Problem
Existing media streaming technologies face challenges in efficiently encoding and transmitting multi-channel audio streams with associated metadata, ensuring audio quality, minimizing bandwidth usage, and maintaining compatibility with diverse playback devices and setups, while managing various types of metadata such as audio descriptions, multi-lingual tracks, and subtitles.
Innovation Solution
A system and method for channel layout evaluation using a channel detective service that performs metadata extraction, identifies discrepancies, and employs a similarity model for layout detection, annotates language and service type, and updates metadata representation for optimal streaming based on identified mix groups and service types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-channel audio streams with metadata are encoded and transmitted, then audio quality and user experience are improved, but bandwidth usage increases
Solution Approach 1:
The patent extracts and processes metadata separately from the audio stream using the channel detective service. By identifying channel layouts, languages, and service types through metadata analysis rather than transmitting complete audio data for all channels, the system reduces bandwidth requirements while maintaining audio quality through intelligent selection and synthesis of channel information.
Solution Approach 2:
The channel detective service performs multiple functions including channel layout detection, language identification, service type classification, and metadata synthesis. This multi-functional approach consolidates what would otherwise require separate processing systems, improving efficiency and reducing the overall bandwidth needed for audio stream transmission.
2Adaptability or versatility
If multiple channel layouts and metadata types are supported, then adaptability to diverse devices and preferences is improved, but system complexity increases
Solution Approach 1:
The patent segments the audio channel detection and metadata processing into distinct functional modules within the channel detective service. Each module handles specific tasks such as channel layout identification, language detection, or service type classification independently, making the complex system more manageable and easier to implement while maintaining high adaptability to diverse playback devices.
Solution Approach 2:
The channel detective service acts as an intermediary layer between the audio stream and the playback device. It processes and interprets complex multi-channel audio data and metadata, translating them into standardized representations that can be universally understood by different playback devices, thereby reducing the complexity at the device level while maintaining system versatility.
3Measurement precision
If manual channel layout analysis is performed, then accuracy of layout detection is improved, but processing time increases
Solution Approach 1:
The channel detective service performs self-service analysis by automatically detecting channel layouts, languages, and service types directly from the audio stream metadata without requiring manual intervention. The system uses built-in algorithms to analyze channel characteristics and generate accurate layout information autonomously, maintaining high detection accuracy while significantly reducing processing time compared to manual analysis methods.
Data Source
AI summary
A system and method for channel layout evaluation including: a computer processor and a channel detective service executing on the computer processor and including functionality to: receive a request to perform channel layout evaluation on a media item including a provided set of channels; perform metadata extraction on the media item to generate a metadata representation of the media item and to identify at least one channel layout discrepancy of the provided set of channels; perform layout detection using the metadata representation by executing a similarity model configured to generate a mix group comprising at least a subset of the provided set of channels, annotating a primary language of the mix group, and annotating a service type of the mix group; and updating the metadata representation with the annotated mix group, wherein the updated metadata representation is provided for streaming the media item.