Audio Fingerprinting Using Combined Peak Sets and Inverted Indexes
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Solution Overview
Problem
Conventional audio fingerprinting techniques face challenges in accuracy due to noisy and distorted audio segments, and scalability issues when handling large databases, requiring efficient indexing and search algorithms.
Innovation Solution
A method involving multiple sliding windows to generate combined peak sets for audio segments, using Constant-Q Transform (CQT) and Discrete Fourier Transform (DFT) routines, and inverted indexing for efficient retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional audio fingerprinting techniques are used, then the process is simple, but accuracy deteriorates due to noisy and distorted audio segments
Solution Approach 1:
The audio signal is divided into multiple overlapping sliding windows, each processed independently through CQT and DFT to generate peak sets. This segmentation allows the system to handle noisy and distorted segments by combining results from multiple windows, thereby improving overall fingerprint accuracy without requiring complete signal perfection.
Solution Approach 2:
Multiple peak sets generated from different sliding windows are merged into a combined peak set through intersection operations. This merging process consolidates reliable frequency information across multiple segments while filtering out spurious peaks from noisy portions, enhancing fingerprint robustness against audio degradation.
2Productivity
If conventional audio fingerprinting techniques are used, then the implementation is simple, but scalability deteriorates when handling large databases
Solution Approach 1:
The system pre-processes audio segments by extracting peaks and generating fingerprints before storage. This preliminary action organizes data in advance, enabling fast retrieval operations later. The inverted index is built using these pre-extracted features, allowing efficient search without reprocessing the entire database during query time.
Solution Approach 2:
An inverted index structure serves as an intermediary between the raw audio database and retrieval queries. The index maps fingerprint features to document identifiers, enabling rapid lookup and filtering. This intermediary structure decouples the complexity of storing and processing large audio databases from the simplicity of retrieval operations.
3Measurement precision
If multiple sliding windows are applied to generate combined peak sets, then accuracy improves, but processing time increases
Solution Approach 1:
The system applies a limited number of sliding windows (e.g., 3-5 overlapping windows) rather than exhaustively processing the entire audio signal with maximum overlap. This partial action approach generates sufficient peak sets to achieve high accuracy while controlling processing time, avoiding the excessive computation that would result from analyzing every possible segment.
Data Source
AI summary
Methods, processors, systems for audio fingerprinting and retrieval are disclosed. One method includes receiving the audio segment generating a first set of peaks by applying a first sliding window on the audio segment, generating a second set of peaks by applying a second sliding window on the audio segment, generating a combined set of peaks based on the first and second sets of peaks, and generating the fingerprint for the audio segment using the combined set of peaks. Another method includes accessing a first inverted index using the sequence of query hashes, determining a temporally compatible sub-sequence of query hashes in the sequence using data retrieved from the first inverted index, accessing a second inverted index using only the temporally compatible sub-sequence, and retrieving data indicative of the target stored audio segment. Another method for target stored digital items is also disclosed.