Cascaded all-pass filters with randomized center frequencies and phase polarity for acoustic and speech measurement and data augmentation (2010.13185v2)

Abstract: We introduce a new member of TSP (Time Stretched Pulse) for acoustic and speech measurement infrastructure, based on a simple all-pass filter and systematic randomization. This new infrastructure fundamentally upgrades our previous measurement procedure, which enables simultaneous measurement of multiple attributes, including non-linear ones without requiring extra filtering nor post-processing. Our new proposal establishes a theoretically solid, flexible, and extensible foundation in acoustic measurement. Moreover, it is general enough to provide versatile research tools for other fields, such as biological signal analysis. We illustrate using acoustic measurements and data augmentation as representative examples among various prospective applications. We open-sourced MATLAB implementation. It consists of an interactive and real-time acoustic tool, MATLAB functions, and supporting materials.

• The paper presents CAPRICEP, a new cascaded all-pass filter framework with randomization for acoustic measurement and data augmentation.
• CAPRICEP employs randomized frequency intervals and impulse response optimization via Wasserstein distance to enable robust and simultaneous acoustic component measurement.
• CAPRICEP is also useful for data augmentation, generating varied audio samples for training deep learning models in audio analysis and speech synthesis.

Overview of "Cascaded all-pass filters with randomized center frequencies and phase polarity for acoustic and speech measurement and data augmentation"

This paper presents a novel approach to acoustic measurement and data augmentation by introducing CAPRICEP (Cascaded All-Pass Filters with Randomized Center Frequencies and Phase Polarities). CAPRICEP is designed to augment the Time Stretched Pulse (TSP) family, which includes well-established signal processing methods like pseudo-random noise and swept-sine signals. The authors, Hideki Kawahara and Kohei Yatabe, propose a new signal processing framework rooted in all-pass filter techniques and randomization to significantly enhance the flexibility and functionality of acoustic measurements.

Technical Contribution

The core innovation in this work is the use of cascaded all-pass filters with randomized parameters to create unit-CAPRICEPs. Unlike traditional FVN (Frequency domain variant of Velvet Noise), which relies on heuristics and has theoretical limitations, CAPRICEP offers a theoretically robust design with fewer tuning parameters. This methodological shift addresses limitations in FVN by simplifying the design space and enhancing the ability to achieve a desired group delay directly.

Key technical advancements include:

• Randomized Frequency Intervals: The authors utilize systematic randomization of frequency intervals between the poles of the all-pass filters, introducing two random variables to enhance the stochastic nature of the impulse response.
• Optimized Impulse Response Design: CAPRICEPs are engineered by optimizing the distribution shape of the impulse response using Wasserstein distance, aiming for specific temporal locality and orthogonal characteristics that make them highly adaptable for acoustic measurements.
• Simultaneous Measurements: The CAPRICEP framework is capable of enabling simultaneous measurement of linear, non-linear, and random components of acoustic responses without additional hardware. This is particularly useful in environments with non-linear and temporally variable characteristics.

Practical and Theoretical Implications

The introduction of CAPRICEP has broad implications for both acoustic measurement and generalized signal processing tasks. Practically, CAPRICEP-based tools could improve the precision of acoustic measurements in various applications, from concert halls to automotive interiors. The capability to efficiently measure non-linear and time-varying acoustic characteristics without additional apparatus is particularly valuable in dynamic environments.

Theoretically, CAPRICEP provides a new lens for exploring auditory perception mechanisms. The paper suggests potential utility in fields such as biological system analysis, where inherent non-linearity and variability necessitate robust measurement techniques.

Data Augmentation and Beyond

Another significant implication of CAPRICEP is in data augmentation for audio-related applications. The ability to produce multiple perceptually indistinguishable yet signal-varied samples from an original recording creates a powerful tool for enhancing datasets, which is crucial for training data-intensive deep learning models in audio analysis and speech synthesis.

Future Directions

While CAPRICEP offers a strong foundation for future exploration, several research avenues remain. Further refining the adaptability of unit-CAPRICEPs to specific frequency-dependent applications could enhance their utility. Investigating the role of randomization parameters in shaping auditory perception models might offer deeper insights into human auditory processing frameworks. Additionally, expanding the implementation of CAPRICEP across varied signal processing platforms may reveal new applications in other domains.

In conclusion, CAPRICEP contributes fundamentally to the field of acoustic measurement by offering a robust, theoretically sound framework for simultaneous measurement and data augmentation. The open-source availability of related tools underscores its potential impact and broad applicability, providing a critical resource for researchers and practitioners in acoustic signal processing.