Neural Network Sound Categorization for Faster SFX Search
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Solution Overview
Problem
Existing sound databases for movies and videogames require extensive manual categorization and familiarity with the database scheme, making it difficult for new content creators to find and add sounds efficiently.
Innovation Solution
A multi-tiered sound categorization system using neural networks that learns sound categorization based on acoustic properties, enabling automatic classification and search of sound effects (SFX) through hierarchical classification and haptic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual categorization of sound databases is used, then sound files can be organized and accessed, but extensive time and familiarity with the categorization scheme are required
Solution Approach 1:
The patent replaces manual mechanical categorization with an automated neural network system. The neural network automatically analyzes audio features of sound files and assigns them to appropriate categories and subcategories, eliminating the need for manual classification while maintaining organized access to sound files.
Solution Approach 2:
The sound database system performs self-categorization through the neural network, which automatically processes new sound files upon upload, determines their categories and subcategories based on acoustic properties, and organizes them without human intervention. This self-service mechanism continuously maintains the database organization.
2Reliability
If new custom sounds are added to the database manually, then the database remains comprehensive, but extensive time and expertise are required
Solution Approach 1:
The manual process of adding and categorizing new sounds is replaced by an automated neural network system. When new sound files are uploaded, the neural network automatically analyzes their acoustic properties, determines appropriate categories and subcategories, and integrates them into the database, maintaining comprehensiveness while dramatically increasing productivity.
3Measurement precision
If detailed hierarchical categorization is implemented, then sound files can be precisely classified, but the complexity of the categorization scheme increases
Solution Approach 1:
The categorization scheme is segmented into multiple hierarchical levels: broad categories (e.g., environmental sounds, mechanical sounds) and more specific subcategories (e.g., nature sounds, animal sounds). This segmentation allows precise classification while managing complexity by breaking down the classification task into manageable hierarchical stages that the neural network processes sequentially.
Data Source
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AI summary
A system method and computer program product for hierarchical categorization of sound comprising one or more neural networks implemented on one or more processors. The one or more neural networks are configured to categorize a sound into a two or more tiered hierarchical course categorization and a finest level categorization in the hierarchy. The categorization sound may be used to search a database for similar or contextually related sounds.