Audio Fingerprint Speaker Identification System
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Solution Overview
Problem
In multi-party communications sessions, identifying the current speaker can be challenging, especially when multiple speakers share a single client device or use telephones, as visual indicators based on account information are insufficient and may lead to confusion about who is speaking.
Innovation Solution
A computer system that generates an audio fingerprint of the current speaker and performs automated speaker recognition by comparing it against stored fingerprints, providing metadata to client devices to identify the speaker and enhance user interfaces with real-time speaker information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual indicators based on account information are used to identify speakers, then the system is simple to operate, but speaker identification becomes inaccurate when multiple speakers share a single client device
Solution Approach 1:
The patent replaces visual indicators based on account information with audio fingerprinting technology. The system generates unique audio fingerprints from speakers' voice characteristics and compares them against a database of stored fingerprints to automatically identify speakers. This substitutes the mechanical/account-based identification system with an acoustic-based automated recognition system, achieving accurate speaker identification even when multiple speakers share a single client device.
2Measurement precision
If automated speaker recognition is implemented, then speaker identification accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-generating and storing audio fingerprints in a database before actual speaker identification is needed. When a speaker speaks, the system only needs to compare the current audio fingerprint against the pre-stored ones, significantly reducing processing time. This preliminary preparation of fingerprint data enables fast real-time speaker recognition without requiring complex on-the-fly analysis.
3Measurement precision
If audio fingerprinting is used for speaker recognition, then speaker identification becomes accurate, but the system requires more computational resources
Solution Approach 1:
The system extracts only the essential acoustic features from audio signals to create compact audio fingerprints, rather than processing entire audio streams. By extracting and storing only the distinctive fingerprint characteristics in a database, the system reduces computational energy requirements for speaker identification while maintaining high accuracy. This extraction of essential features minimizes the computational burden during real-time recognition.
Data Source
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AI summary
A computer system may communicate metadata that identifies a current speaker. The computer system may receive audio data that represents speech of the current speaker, generate an audio fingerprint of the current speaker based on the audio data, and perform automated speaker recognition by comparing the audio fingerprint of the current speaker against stored audio fingerprints contained in a speaker fingerprint repository. The computer system may communicate data indicating that the current speaker is unrecognized to a client device of an observer and receive tagging information that identifies the current speaker from the client device of the observer. The computer system may store the audio fingerprint of the current speaker and metadata that identifies the current speaker in the speaker fingerprint repository and communicate the metadata that identifies the current speaker to at least one of the client device of the observer or a client device of a different observer.