Impulse response and reverberation time measurements using a periodic pseudorandom sequence

1988 ◽  
Vol 84 (S1) ◽  
pp. S64-S64
Author(s):  
W. T. Chu
Keyword(s):  
Impulse Response ◽  
Pseudorandom Sequence ◽  
Reverberation Time

Quantifying Non-Linearity in Early Decay Curves of Measured and Computer-Modeled Room Impulse Responses of a Highly Non-Diffuse Room Exhibiting Flutter Echo

2020 ◽  
Author(s):  
Heather L. Lai ◽  
Brian Hamilton
Keyword(s):  
Linear Regression ◽  
Computer Modeling ◽  
Impulse Response ◽  
Decay Curve ◽  
Sound Field ◽  
Energy Decay ◽  
Room Acoustics ◽  
Reverberation Time ◽  
Sound Fields ◽  
Regression Curves

Abstract This paper investigates the use of two room acoustics metrics designed to evaluate the degree to which the linearity assumptions of the energy density curves are valid. The study focuses on measured and computer-modeled energy density curves derived from the room impulse response of a space exhibiting a highly non-diffuse sound field due to flutter echo. In conjunction with acoustical remediation, room impulse response measurements were taken before and after the installation of the acoustical panels. A very dramatic decrease in the reverberation time was experienced due to the addition of the acoustical panels. The two non-linearity metrics used in this study are the non-linearity parameter and the curvature. These metrics are calculated from the energy decay curves computed per octave band, based on the definitions presented in ISO 3382-2. The non-linearity parameter quantifies the deviation of the EDC from a straight line fit used to generated T20 and T30 reverberation times. Where the reverberation times are calculated based on a linear regression of the data relating to either −5 to −25 dB for T20 or −5 to −35 dB for T30 reverberation time calculations. This deviation is quantified using the correlation coefficient between the energy decay curve and the linear regression for the specified data. In order to graphically demonstrate these non-linearity metrics, the energy decay curves are plotted along with the linear regression curves for the T20 and T30 reverberation time for both the measured data and two different room acoustics computer-modeling techniques, geometric acoustics modeling and finite-difference wave-based modeling. The intent of plotting these curves together is to demonstrate the relationship between these metrics and the energy decay curve, and to evaluate their use for quantifying degree of non-linearity in non-diffuse sound fields. Observations of these graphical representations are used to evaluate the accuracy of reverberation time estimations in non-diffuse environments, and to evaluate the use of these non-linearity parameters for comparison of different computer-modeling techniques or room configurations. Using these techniques, the non-linearity parameter based on both T20 and T30 linear regression curves and the curvature parameter were calculated over 250–4000 Hz octave bands for the measured and computer-modeled room impulse response curves at two different locations and two different room configurations. Observations of these calculated results are used to evaluate the consistency of these metrics, and the application of these metrics to quantifying the degree of non-linearity of the energy decay curve derived from a non-diffuse sound field. These calculated values are also used to evaluate the differences in the degree of diffusivity between the measured and computer-modeled room impulse response. Acoustical computer modeling is often based on geometrical acoustics using ray-tracing and image-source algorithms, however, in non-diffuse sound fields, wave based methods are often able to better model the characteristic sound wave patterns that are developed. It is of interest to study whether these improvements in the wave based computer-modeling are also reflected in the non-linearity parameter calculations. The results showed that these metrics provide an effective criteria for identifying non-linearity in the energy decay curve, however for highly non-diffuse sound fields, the resulting values were found to be very sensitive to fluctuations in the energy decay curves and therefore, contain inconsistencies due to these differences.

Permissible number of synchronous averaging times to obtain reverberation time from impulse response under time‐variance conditions

2006 ◽  
Vol 120 (5) ◽  
pp. 3223-3224
Author(s):  
Fumiaki Satoh ◽  
Yukiteru Hayashi ◽  
Shinichi Sakamoto ◽  
Hideki Tachibana
Keyword(s):  
Impulse Response ◽  
Reverberation Time ◽  
Time Variance

scholarly journals COMPENSATION OF THE EFFECTS OF SOUND PROPAGATION CHANNEL IN UNDERWATER ACOUSTIC SYSTEMS

2020 ◽  
Author(s):  
С.А. Пахомов ◽  
С.В. Шостак
Keyword(s):  
Impulse Response ◽  
Sound Propagation ◽  
Weight Coefficient ◽  
Minimum Variance ◽  
Necessary Condition ◽  
Pseudorandom Sequence ◽  
Noise Component ◽  
Underwater Acoustic ◽  
Markov Theorem ◽  
The Media

Состояние гидроакустического канала распространения звука зависит от множества случайных факторов среды. Для учета влияния такого канала на передаваемый сигнал может использоваться метод линейной фильтрации, в рамках которого канал представляется в виде линейной инвариантной системы с аддитивным гауссовским шумом, где связь между сигналами на входе и выходе описывается импульсной характеристикой. Необходимыми условиями эффективности применения данного метода являются выбор входного сигнала и оценка весовых коэффициентов используемой системы, что в работе выполнено на основе теоремы Гаусса–Маркова. При решении задачи получены несмещенные оценки с минимальной дисперсией, в том числе для случая применения в качестве входного сигнала псевдослучайной последовательности. Предложен метод компенсации влияния канала с учетом знания его импульсной характеристики, позволяющий уменьшать уровень шумовой составляющей. The state of the underwater acoustic channel depends on a variety of random factors of the media. Estimation of the influence of such channel on the transmitting signal can be performed by the method of linear filtration. It considers channel as a linear non-variant system with additive Gaussian noise, where the relation between input and output signals is described by impulse response. The necessary condition of efficient implementation of this method is the selection of valid input signals and estimation of the weight coefficient of the implemented system, which was performed using Gauss–Markov theorem in the present work. Following the results of solving the problem, the minimum variance unbiased estimates were obtained, including the case of using the pseudorandom sequence as an input signal. At long last, the paper presents the method of channel influence compensation with consideration of known impulse response, which allows reducing the level of the noise component.

scholarly journals EFEK REVERB TIPE LECTURE HALL DENGAN PENDEKATAN TEORI SABINE BERBASIS DIGITAL SIGNAL PROCESSOR (DSPs)

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Marisa Premitasari ◽  
Hendi Handian
Keyword(s):  
Impulse Response ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Infinite Impulse Response ◽  
Lecture Hall ◽  
Reverberation Time ◽  
Signal Processor

Salah satu jenis efek musik adalah reverb, yang merupakan hasil tiruan dari refleksi bunyi di dalam ruangan dimana sebagian bunyi akan terabsorpsi dan kemudian terjadi pemantulan bunyi yang berulang-ulang . Sesuai dengan tipe ruangannya, lecture hall didisain supaya tidak mengganggu suara dosen ketika sedang berbicara dimana sebuah pendekatan bernama teori Sabine mempunyaidelay di bawah satu detik. Teori ini akan direalisasikan menggunakan DSPs dengan input gitar elektrik .Perancangan efek dengan pendekatan Sabine disusun berdasarkan tiga subsistem yaitu Early Refelction, Butterworth dan Reverberation. Masing-masing subsistem menggunakan pemfilteran Infinite Impulse Response(IIR) dan total hasil efek reverb dilakukan pemrosesan CombFilter. Realisasi dijalankan dengan menggunakan duah buah PC dimana PC pertama untuk mengeksekusi program dan PC kedua untuk analisis hasil keluaran yang dicatat melalui dua buah professional software. CUBASE SX3 mencatat hasil dengan spesifikasi frekuensi Sabine dan ADOBE AUDITION 2.0 mencatat hasil dengan spesifikasi waktu Sabine. Hasil Eksekusi program sementara menunjukkan terjadinya error terhadap pendekatan Teori Sabine. Untuk spesifikasi frekuensi Sabine (faktor penguatan) error terbesar terletak pada frekuensi Sabine 2000 Hz sebesar 2.57 (frekuensi input 4000 Hz) dan 2.64 (frekuensi input 9600 Hz) sementara spesifikasi waktu Sabine (reverberation time) menunjukkan error 9.057 dengan frekuensi input 8000 Hz.

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