Simultaneous measurement of time-invariant linear and nonlinear, and random and extra responses using frequency domain variant of velvet noise

We introduce a new acoustic measurement method that can measure the linear time-invariant response, the nonlinear time-invariant response, and random and time-varying responses simultaneously. The method uses a set of orthogonal sequences made from a set of unit FVNs (Frequency domain variant of Velvet Noise), a new member of the TSP (Time Stretched Pulse). FVN has a unique feature that other TSP members do not. It is a high degree of design freedom that makes the proposed method possible without introducing extra equipment. We introduce two useful cases using two and four orthogonal sequences and illustrates their use using simulations and acoustic measurement examples. We developed an interactive and realtime acoustic analysis tool based on the proposed method. We made it available in an open-source repository. The proposed response analysis method is general and applies to other fields, such as auditory-feedback research and assessment of sound recording and coding.

[1]  Yutaka Kaneda,et al.  A Recursive Adaptive Method of Impulse Response Measurement with Constant SNR over Target Frequency Band , 2013 .

[2]  Dario D'Orazio,et al.  Impulse Responses Measured with MLS or Swept-Sine Signals Applied to Architectural Acoustics: An In-depth Analysis of the Two Methods and Some Case Studies of Measurements Inside Theaters , 2015 .

[3]  Guy-Bart Stan,et al.  Comparison of different impulse response measurement techniques , 2002 .

[4]  N. Aoshima.  Computer‐generated pulse signal applied for sound measurement , 1981 .

[5]  Anders Löfqvist,et al.  Toward a consensus on symbolic notation of harmonics, resonances, and formants in vocalization. , 2015, The Journal of the Acoustical Society of America.

[6]  Hideki Kawahara,et al.  Interactions between speech production and perception under auditory feedback perturbations on fundamental frequencies , 1994 .

[7]  Hideki Kawahara,et al.  Frequency domain variant of Velvet noise and its application to acoustic measurements , 2019, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

[8]  Vesa Välimäki,et al.  A Perceptual Study on Velvet Noise and Its Variants at Different Pulse Densities , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[9]  M. Schroeder.  Integrated‐impulse method measuring sound decay without using impulses , 1979 .

[10]  Angelo Farina,et al.  Simultaneous Measurement of Impulse Response and Distortion with a Swept-Sine Technique , 2000 .

[11]  Tomoki Toda,et al.  A New Cosine Series Antialiasing Function and its Application to Aliasing-Free Glottal Source Models for Speech and Singing Synthesis , 2017, INTERSPEECH.

[12]  A. Nuttall.  Some windows with very good sidelobe behavior , 1981 .

[13]  Hideki Kawahara,et al.  Effects of auditory feedback on F0 trajectory generation , 1996, ICSLP.

[14]  Hirokazu Kameoka,et al.  Progress in LPC-based frequency-domain audio coding , 2016 .

[15]  H. Pollak,et al.  Prolate spheroidal wave functions, fourier analysis and uncertainty — III: The dimension of the space of essentially time- and band-limited signals , 1962 .

[16]  Svante Granqvist,et al.  Guidelines for selecting microphones for human voice production research. , 2010, American journal of speech-language pathology.

[17]  Johan Sundberg,et al.  Significance of auditory and kinesthetic feedback to singers' pitch control. , 2002, Journal of voice : official journal of the Voice Foundation.

[18]  Rita R. Patel,et al.  Recommended Protocols for Instrumental Assessment of Voice: American Speech-Language-Hearing Association Expert Panel to Develop a Protocol for Instrumental Assessment of Vocal Function. , 2018, American journal of speech-language pathology.

[19]  Swen Müller,et al.  Transfer-Function Measurement with Sweeps , 2001 .

[20]  F. Itakura,et al.  A statistical method for estimation of speech spectral density and formant frequencies , 1970 .

[21]  Malcolm J. Hawksford,et al.  Distortion immunity of MLS-derived impulse response measurements , 1993 .

[22]  D. Slepian,et al.  Prolate spheroidal wave functions, fourier analysis and uncertainty — II , 1961 .

[23]  Tomoki Toda,et al.  Frequency domain variants of velvet noise and their application to speech processing and synthesis: with appendices , 2018, INTERSPEECH.

[24]  Susanna Spinsante,et al.  A Swept-Sine Pulse Compression Procedure for an Effective Measurement of Intermodulation Distortion , 2020, IEEE Transactions on Instrumentation and Measurement.

[25]  L. H. Anauer,et al.  Speech Analysis and Synthesis by Linear Prediction of the Speech Wave , 2000 .

[26]  Yasuhiro Oikawa,et al.  Maximally Energy-Concentrated Differential Window for Phase-Aware Signal Processing Using Instantaneous Frequency , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[27]  Matti Karjalainen,et al.  Reverberation Modeling Using Velvet Noise , 2007 .