Speech Characterization via Synthetic Reference Audio Signals
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Solution Overview
Problem
Conventional speech characterization techniques require numerous audio samples to establish accuracy and precision, making them inefficient and labor-intensive, especially in identifying speaker-specific features such as emotional state and health conditions.
Innovation Solution
A system that generates synthetic reference audio signals with the same content as the given audio signal, allowing for the removal of deterministic features and the identification of speaker-specific features by subtracting feature vectors from the given and synthetic signals, enabling efficient and autonomous speech characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional speech characterization techniques are used, then accuracy and precision can be achieved, but numerous audio samples are required making the process inefficient and labor-intensive
Solution Approach 1:
The patent creates synthetic reference audio signals that replicate the content and deterministic features of the input speech while embodying specific speaker characteristics. These synthetic copies serve as reference models for comparison, enabling the system to identify speaker-specific features without requiring extensive audio samples. The synthetic signal acts as a template that captures essential speaker attributes in a controlled manner.
Solution Approach 2:
The patent extracts and removes deterministic features (content-related characteristics) from both the input audio signal and synthetic reference signal through feature vector subtraction. This extraction process isolates the speaker-specific features from the content-dependent features, allowing accurate speech characterization with minimal samples. By taking out the deterministic components, the system focuses only on the unique speaker characteristics.
2Reliability
If conventional techniques require numerous audio samples, then comprehensive speaker analysis is possible, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent performs preliminary synthesis of reference audio signals that embody expected speaker characteristics before comparing them with the actual input signal. This preliminary action creates a reference framework in advance, allowing the system to quickly identify deviations and speaker-specific features without needing to process numerous audio samples. The synthetic reference signal is prepared beforehand to guide the comparison process.
Solution Approach 2:
The patent transforms the speech analysis problem by changing from analyzing raw audio signals directly to comparing feature vectors derived from synthetic and actual signals. By transforming the data into feature vector space and performing subtraction operations, the system achieves reliable speaker characterization with fewer samples and reduced processing time. The parameter transformation enables more efficient computation.
3Measurement precision
If extensive audio samples are used for speech characterization, then accurate speaker profiling is achieved, but the system becomes complex and computationally intensive
Solution Approach 1:
The patent replaces the mechanical approach of collecting and processing numerous audio samples with a computational approach using synthetic signal generation and feature vector mathematics. Instead of physically accumulating large datasets, the system uses algorithmic synthesis and vector subtraction to achieve the same analytical goal with simpler operations. This substitution reduces system complexity while maintaining detection precision.
Data Source
AI summary
Techniques regarding speech characterization are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a speech analysis component that can determine a condition of an origin of an audio signal based on a difference between a first feature of the audio signal and a second feature of a synthesized reference audio signal.