Speaker Enrollment Using Sound Localization and Face Matching
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Solution Overview
Problem
Conventional speaker enrollment processes are complicated by the need for additional steps like voiceprint recognition and are prone to failure due to obscured faces or mask-wearing, making lip motion-based methods unreliable.
Innovation Solution
An automated speaker enrollment system using a camera and microphone array to capture images and audio, employing sound localization and facial recognition to accurately identify and record speech of a target speaker within a valid geometric range, generating speaker features for enrollment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If lip motion-based speaker identification is used, then speaker selection can be automated, but the system becomes unreliable when faces are obscured or speakers wear masks
Solution Approach 1:
The patent combines audio-based sound localization with visual facial recognition to create a hybrid speaker identification system. The audio component detects speaker direction through microphone arrays, while the visual component captures facial images, and both are integrated to reliably identify the target speaker within the effective geometric range, overcoming the limitation of mask-wearing scenarios.
Solution Approach 2:
The patent introduces an intermediary validation mechanism that cross-checks audio-derived speaker direction with visual facial position. This intermediary step verifies whether the detected face corresponds to the sound source direction, providing a reliable confirmation that works even when visual features are partially obscured by masks.
2Measurement precision
If voiceprint recognition model is applied for speaker enrollment, then speaker features can be extracted, but the system complexity increases with additional setting steps
Solution Approach 1:
The patent implements a self-service enrollment system where the speaker is automatically identified and enrolled without manual intervention. The system autonomously detects the speaker through sound localization, captures their speech, extracts speaker features, and completes enrollment automatically, eliminating the need for users to manually configure voiceprint recognition models or perform complex enrollment procedures.
Solution Approach 2:
The patent replaces manual enrollment operations with automated acoustic and visual detection systems. Instead of requiring users to manually set up voiceprint models, the system uses microphone arrays for sound localization and cameras for facial recognition to automatically identify and enroll speakers, substituting mechanical interaction with automated sensing and processing.
3Measurement precision
If facial recognition is used to determine recording timing, then target speaker can be identified, but the system fails when the speaker's face is obscured or they turn away
Solution Approach 1:
The patent creates a multi-functional identification system that serves multiple purposes: audio-based sound localization identifies speaker direction, visual facial recognition confirms facial position, and their integration provides robust speaker identification. This universal approach works whether the speaker's face is visible or obscured, as the audio component continues to function independently.
Solution Approach 2:
The patent prepares for potential face occlusion by having the audio-based sound localization system ready as a backup mechanism. Before visual recognition can fail due to masks or turned-away faces, the audio system is already detecting speaker direction, providing a cushion against visual recognition failure and ensuring continuous reliable speaker identification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately determines the target speaker even with obscured faces or masks, reducing complexity and enhancing speech quality for effective enrollment.
Implementation Method 1
Sound localization is performed for estimating a sound source direction
Implementation Method 2
the facial position of at least one person includes a distance being estimated based on a focus distance of the camera from the face of the at least one person
Data Source
AI summary
A method and a system for automated speaker enrollment are provided. In the method, a camera is used to capture image data so that a facial position of a person can be recognized, a microphone array is used to generate speech data, and a sound localization technology is used to estimate a sound source direction. A target speaker can be determined by matching the facial position and the direction toward the sound source, and more particularly whether the target speaker is within a valid geometric range. After that, the speech produced by the target speaker along a target speaker direction is recorded, and the speech can be enhanced for generating speaker features with respect to the target speaker for enrolling to a specific system.