Sound Search Using Caption Embeddings for Semantic Audio Retrieval
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Solution Overview
Problem
Current technologies lack effective methods for searching and retrieving specific sounds from media files, as existing solutions are inadequate for handling the increasing volume of audio content and do not utilize natural language descriptions efficiently.
Innovation Solution
A system that generates query caption embeddings based on user queries and selects corresponding sound captions from a media file repository using similarity metrics, allowing for the retrieval of media files with semantically similar sound descriptions, even if the query does not exactly match existing captions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword-based search methods are used for audio content, then the search process is simple, but the search accuracy and relevance are insufficient
Solution Approach 1:
The patent introduces caption embeddings as an intermediary representation that bridges the gap between audio content and text queries. Audio captions are generated from media files, converted to embeddings, and stored for efficient similarity comparison with query embeddings, thereby improving search accuracy without requiring direct complex audio analysis during search operations
Solution Approach 2:
The patent replaces traditional mechanical keyword-matching search mechanisms with semantic similarity comparison using embedding vectors. Instead of exact keyword matching, the system uses cosine similarity or other distance metrics on embedding spaces to find semantically relevant audio content, significantly improving search precision
2Adaptability or versatility
If exact keyword matching is used for sound search, then the system is fast and simple, but it cannot handle semantic variations or paraphrases
Solution Approach 1:
The patent performs preliminary processing by generating audio captions from media files and converting them to embeddings in advance, before any search queries are made. These pre-computed caption embeddings are stored and ready for rapid comparison with query embeddings, enabling fast semantic search without real-time audio processing
Solution Approach 2:
The patent transforms audio content into a different parameter space (text captions) and then into embedding vectors, changing the representation parameters from raw audio waveforms to semantic vector spaces. This allows semantic variations and paraphrases to be captured through vector similarity rather than exact string matching
3Loss of information
If audio content is stored with detailed metadata for better searchability, then search relevance improves, but storage requirements and processing complexity increase
Solution Approach 1:
The patent extracts only the essential semantic information from audio content by generating concise audio captions that describe the dominant sounds. Instead of storing and processing entire audio files or comprehensive metadata, the system extracts and stores only the caption embeddings, significantly reducing storage requirements while maintaining search capability
Solution Approach 2:
The patent creates a simplified copy of audio content in the form of text captions and their embedding representations. Rather than storing the original large audio files for search purposes, the system stores compact embedding vectors that serve as searchable proxies, reducing storage needs while preserving search functionality
Data Source
AI summary
A device includes one or more processors configured to generate one or more query caption embeddings based on a query. The processor(s) are further configured to select one or more caption embeddings from among a set of embeddings associated with a set of media files of a file repository. Each caption embedding represents a corresponding sound caption, and each sound caption includes a natural-language text description of a sound. The caption embedding(s) are selected based on a similarity metric indicative of similarity between the caption embedding(s) and the query caption embedding(s). The processor(s) are further configured to generate search results identifying one or more first media files of the set of media files. Each of the first media file(s) is associated with at least one of the caption embedding(s).