Synthetic Impulse Response Generation for Audio Dataset Augmentation
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Solution Overview
Problem
Conventional acoustic measurement systems face inefficiencies, inaccuracies, and inflexibilities in capturing and improving digital audio recordings due to complex, time-consuming, and resource-intensive testing procedures, often resulting in incomplete datasets and inaccurate acoustic impulse responses.
Innovation Solution
The development of systems that generate synthetic impulse responses based on modifying direct-to-reverberant ratio (DRR) and reverberation time (T60) parameters, allowing for the creation of augmented datasets and improved digital audio recordings without the need for extensive testing, using techniques such as windowed scalar application and noise floor removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional testing procedures are used to determine acoustic impulse response, then measurement accuracy is improved, but time consumption and equipment cost increase significantly
Solution Approach 1:
The patent creates synthetic impulse responses by copying and transforming existing impulse response data. Instead of performing new physical measurements, the system generates additional training samples by applying transformations (time-stretching, pitch-shifting, mixing) to existing recorded impulse responses, thereby eliminating the need for time-consuming repeated testing while maintaining data quality for machine learning training.
Solution Approach 2:
The patent performs preliminary processing of impulse response data by pre-extracting features, pre-mixing samples, and pre-generating transformed versions of impulse responses. This preliminary action creates a ready-to-use augmented dataset that can be directly fed into machine learning models without requiring additional measurement sessions, thus saving time while ensuring measurement accuracy is preserved through the synthetic generation process.
2Measurement precision
If conventional testing procedures are used to determine acoustic impulse response, then measurement accuracy is improved, but equipment cost and complexity increase
Solution Approach 1:
The patent replaces expensive specialized testing equipment with software-based synthetic generation. By copying existing impulse response recordings and applying computational transformations, the system achieves the same training objective without requiring specialized acoustic measurement hardware, thereby reducing equipment cost and complexity while maintaining the ability to generate accurate training data.
Solution Approach 2:
The patent substitutes mechanical/acoustic testing systems with computational processing. Instead of using physical measurement equipment to capture impulse responses, the system uses software algorithms to generate synthetic impulse responses from existing audio data, replacing complex hardware-based acoustic measurement with software-based signal processing and synthesis.
3Reliability
If conventional testing procedures are used to determine acoustic impulse response, then data quality for machine learning training is improved, but the testing process becomes more resource-intensive
Solution Approach 1:
The patent performs preliminary data augmentation by pre-generating transformed impulse responses (time-stretched, pitch-shifted, mixed versions) and storing them as an augmented training dataset. This preliminary action ensures high-quality diverse training data is available before model training begins, eliminating the need for resource-intensive repeated measurements during the training process itself.
Solution Approach 2:
The patent creates multiple copies and variations of existing impulse response data through transformations. By copying and transforming existing high-quality impulse responses into diverse synthetic samples, the system builds a large, diverse training dataset without requiring proportional increases in measurement resources, thus improving training data quality while controlling computing resource consumption.
4Measurement precision
If acoustic impulse responses are obtained through conventional testing, then accuracy of acoustic measurements is improved, but flexibility of operation is reduced
Solution Approach 1:
The patent implements dynamic impulse response generation where synthetic impulse responses can be adaptively created with varying parameters (different time-stretch factors, pitch-shift amounts, mixing ratios). This dynamic approach allows the system to generate impulse responses tailored to specific training needs and model requirements, providing operational flexibility while maintaining measurement accuracy through controlled transformations of the original acoustic data.
Data Source
AI summary
The disclosure describes one or more embodiments of an impulse response system that generates accurate and realistic synthetic impulse responses. For example, given an acoustic impulse response, the impulse response system can generate one or more synthetic impulse responses that modify the direct-to-reverberant ratio (DRR) of the acoustic impulse response. As another example, the impulse response system can generate one or more synthetic impulse responses that modify the reverberation time (e.g., T60) of the acoustic impulse response. Further, utilizing the synthetic impulse responses, the impulse response system can perform a variety of functions to improve a digital audio recording or acoustic measurement or prediction model.