AI Speaker Tagging With Audio Fingerprints for Time-Synced Navigation

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Solution Overview

Problem

Conventional navigation methods for content items, such as songs or videos, are inaccurate and resource-intensive, lacking temporal information about speakers and contributors, and there is a need for more sophisticated and efficient navigation and speaker identification.

Innovation Solution

Utilizing artificial intelligence to tag, catalog, and retrieve speaker identities by analyzing audio files with deep learning models and audio-fingerprints, enabling precise navigation and identification of speakers through time-synchronized content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional navigation methods (seek bar, fast-forward, rewind) are used to find desired portions of content items, then users can navigate through content, but the navigation is inaccurate, time-consuming, and resource-wasteful

Engineering Contradiction:

Improvenavigation accuracyVSAvoidtime to find desired portion

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary action by pre-generating audio fingerprints for all segments of the content item and storing them in a database before the user needs to navigate. When a user wants to find a specific speaker or sound, the system can immediately search the pre-processed fingerprints without having to analyze the entire audio file in real-time, thus achieving accurate and fast navigation without time loss

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The invention replaces the mechanical manual navigation system (seek bar dragging, fast-forward/rewind button pressing) with an automated acoustic fingerprint matching system. Instead of mechanically scrolling through content, the system uses audio feature extraction, fingerprint generation, and database searching to automatically locate desired portions, dramatically improving both accuracy and speed while reducing user effort and time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If conventional navigation methods are used, then users can play content items, but the process is inefficient and consumes excessive computing resources

Engineering Contradiction:

Improvenavigation efficiencyVSAvoidcomputing resource consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system divides the content item into multiple segments and generates audio fingerprints for each segment independently. This segmentation allows the navigation system to search only relevant segments rather than processing the entire content item, significantly improving navigation efficiency while reducing computing resource consumption. The segmented approach enables parallel processing and faster database queries

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The invention replaces inefficient manual navigation with an automated acoustic fingerprint-based system that uses pre-extracted audio features. This substitution eliminates the need for real-time audio analysis during navigation, replacing resource-intensive mechanical scrolling with efficient database lookups based on pre-computed acoustic signatures, thereby improving productivity while reducing energy and computing resource usage

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of information

If speaker identities are not tagged in content items, then content can be played conventionally, but users cannot efficiently search for or identify speakers at specific portions

Engineering Contradiction:

Improvespeaker identity informationVSAvoidsystem complexity for speaker identification

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system performs preliminary action by automatically detecting and tagging speaker identities in content items during the content processing phase, before users need to search or identify speakers. Audio fingerprints are generated and associated with speaker identities in advance, stored in a database, making speaker information readily available without adding complexity during the actual playback or search operations

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The invention introduces an intermediary layer - the audio fingerprint database - that bridges the gap between raw audio content and speaker identity information. Instead of directly analyzing audio waves during playback to identify speakers, the system uses pre-generated acoustic fingerprints as intermediaries to match and identify speakers, significantly reducing the computational complexity while preserving complete speaker identity information

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20260004787A1Method and System for Tagging, Cataloging, and Retrieving Speaker Identities Using Artificial Intelligence on Time-Synchronized Content

Publication Date: 2026.01.01 MUSIXMATCH SPA

AI summary

In one embodiment, a computer-implemented method includes receiving, at one or more processing devices, an audio file, tagging, using an artificial intelligence engine, one or more portions of the audio file to generate a modified audio file, wherein the tagging is performed based on the one or more portions corresponding to an audio-fingerprint of a voice stored in a database, performing dynamic cluster adaptation on the modified audio file, and causing the modified audio file to be played via a computing device.