Direct-to-reverberant Energy Ratio Research Articles

Acoustic SLAM Based on the Direction-of-Arrival and the Direct-to-Reverberant Energy Ratio

This paper proposes a new method that fuses acoustic measurements in the reverberation field and low-accuracy inertial measurement unit (IMU) motion reports for simultaneous localization and mapping (SLAM). Different from existing studies that only use acoustic data for direction-of-arrival (DoA) estimates, the source’s distance from sensors is calculated with the direct-to-reverberant energy ratio (DRR) and applied to eliminate the nonlinear noise from motion reports. A particle filter is applied to estimate the critical distance, which is key for associating the source’s distance with the DRR. A keyframe method is used to eliminate the deviation of the source position estimation toward the robot. The proposed DoA-DRR acoustic SLAM (D-D SLAM) is designed for three-dimensional motion and is suitable for drones. The method is the first acoustic SLAM algorithm that has been validated on a real-world drone dataset that contains only acoustic data and IMU measurements. Compared with previous methods, D-D SLAM has acceptable performance in locating the drone and building a source map from a real-world drone dataset. The average location accuracy is 0.48 m, while the source position error converges to less than 0.25 m within 2.8 s. These results prove the effectiveness of D-D SLAM in real-world scenes.

Cortical auditory distance representation based on direct-to-reverberant energy ratio

Auditory distance perception and its neuronal mechanisms are poorly understood, mainly because 1) it is difficult to separate distance processing from intensity processing, 2) multiple intensity-independent distance cues are often available, and 3) the cues are combined in a context-dependent way. A recent fMRI study identified human auditory cortical area representing intensity-independent distance for sources presented along the interaural axis (Kopco et al. PNAS, 109, 11019-11024). For these sources, two intensity-independent cues are available, interaural level difference (ILD) and direct-to-reverberant energy ratio (DRR). Thus, the observed activations may have been contributed by not only distance-related, but also direction-encoding neuron populations sensitive to ILD. Here, the paradigm from the previous study was used to examine DRR-based distance representation for sounds originating in front of the listener, where ILD is not available. In a virtual environment, we performed behavioral and fMRI experiments, combined with computational analyses to identify the neural representation of distance based on DRR. The stimuli varied in distance (15–100 ​cm) while their received intensity was varied randomly and independently of distance. Behavioral performance showed that intensity-independent distance discrimination is accurate for frontal stimuli, even though it is worse than for lateral stimuli. fMRI activations for sounds varying in frontal distance, as compared to varying only in intensity, increased bilaterally in the posterior banks of Heschl’s gyri, the planum temporale, and posterior superior temporal gyrus regions. Taken together, these results suggest that posterior human auditory cortex areas contain neuron populations that are sensitive to distance independent of intensity and of binaural cues relevant for directional hearing.

Binaural Direct-to-Reverberant Energy Ratio and Speaker Distance Estimation

This article addresses the problem of distance estimation using binaural hearing aid microphones in reverberant rooms. Among several distance indicators, the direct-to-reverberant energy ratio (DRR) has been shown to be more effective than other features. Therefore, we present two novel approaches to estimate the DRR of binaural signals. The first method is based on the interaural magnitude-squared coherence whereas the second approach uses stochastic maximum likelihood beamforming to estimate the power of the direct and reverberant components. The proposed DRR estimation algorithms are integrated into a distance estimation technique. When based solely on DRR, the distance estimation algorithm requires calibration where naturally the critical distance is a good calibration point. We thus propose two approaches for the calibration of the distance estimation algorithm: Informed calibration using the critical distance of the reverberant room and blind calibration using the listener's own voice. Results across various acoustical environments show the benefit of the proposed algorithms for the estimation of sound source distances up to 3 m with an estimation error of about 35 cm using informed calibration and about 1 m using the fully blind calibration strategy.

A dissociation between speech understanding and perceived reverberation

As direct-to-reverberant energy ratio (DRR) decreases or decay time increases, speech intelligibility tends to decrease for both normal-hearing and hearing-impaired listeners. Given this relationship, it is easy to assume that perceived reverberation (reverberance) would act as an intermediary—as physical reverberation increases, so does reverberance, and speech intelligibility decreases as a result. This assumption has not been tested explicitly. Two experiments were conducted to test this hypothesis. In Experiment 1, listeners performed a magnitude estimation task, reporting reverberance for speech stimuli that were convolved with impulse responses whose reverberant properties were manipulated. Listeners reported a decrease in reverberance when the DRR was increased at both ears (Natural Room condition), but not when it was increased at only the ear nearest the source (Hybrid condition). In Experiment 2, listeners performed a speech intelligibility task wherein noise-masked speech was convolved with a subset of the impulse responses from Experiment 1. As predicted by the speech transmission index (STI), speech intelligibility was good in cases where at least one ear received non-reverberant speech, including the Hybrid listening condition in Experiment 1. Thus, the Hybrid listening condition resulted simultaneously in high reverberance (Exp. 1) and high speech intelligibility (Exp. 2), demonstrating that reverberance and speech intelligibility can be dissociated.

Modulation-Domain Kalman Filtering for Monaural Blind Speech Denoising and Dereverberation

We describe a monaural speech enhancement algorithm based on modulation-domain Kalman filtering to blindly track the time–frequency log-magnitude spectra of speech and reverberation. We propose an adaptive algorithm that performs blind joint denoising and dereverberation, while accounting for the inter-frame speech dynamics, by estimating the posterior distribution of the speech log-magnitude spectrum given the log-magnitude spectrum of the noisy reverberant speech. The Kalman filter update step models the non-linear relations between the speech, noise, and reverberation log spectra. The Kalman filtering algorithm uses a signal model that takes into account the reverberation parameters of the reverberation time $T_{60}$ and the direct-to-reverberant energy ratio (DRR) and also estimates and tracks $T_{60}$ and the DRR in every frequency bin to improve the estimation of the speech log spectrum. The proposed algorithm is evaluated in terms of speech quality, speech intelligibility, and dereverberation performance for a range of reverberation parameters and reverberant speech to noise ratios, in different noises, and is also compared to competing denoising and dereverberation techniques. Experimental results using noisy reverberant speech demonstrate the effectiveness of the enhancement algorithm.

Estimating the direct-to-reverberant energy ratio from the coherence between coincident pressure and particle velocity

An analytical expression for the relationship between the direct-to-reverberant energy ratio (DRR) and the coherence estimation function between coincident pressure and particle velocity component is derived. The analytical solution is first validated with simulated room impulse responses and then used to estimate the DRR in five octave bands for several receiver positions measured in a total of 11 rooms of vastly different sizes and acoustic characteristics. The accuracy is evaluated by comparison with the DRR estimated directly from the room impulse response. The difference is typically 5 dB. For two rooms, the variation of the DRR estimate with source-to-receiver position is also shown. The method is blind in the sense that it is virtually independent of the signal generated by a single sound source.

Estimating Direct-to-Reverberant Energy Ratio Using D/R Spatial Correlation Matrix Model

We present a method for estimating the direct-to-reverberant energy ratio (DRR) that uses a direct and reverberant sound spatial correlation matrix model (Hereafter referred to as the spatial correlation model). This model expresses the spatial correlation matrix of an array input signal as two spatial correlation matrices, one for direct sound and one for reverberation. The direct sound propagates from the direction of the sound source but the reverberation arrives from every direction uniformly. The DRR is calculated from the power spectra of the direct sound and reverberation that are estimated from the spatial correlation matrix of the measured signal using the spatial correlation model. The results of experiment and simulation confirm that the proposed method gives mostly correct DRR estimates unless the sound source is far from the microphone array, in which circumstance the direct sound picked up by the microphone array is very small. The method was also evaluated using various scales in simulated and actual acoustical environments, and its limitations revealed. We estimated the sound source distance using a small microphone array, which is an example of application of the proposed DRR estimation method.

Temporal Dynamics for Blind Measurement of Room Acoustical Parameters

In this paper, short- and long-term temporal dynamic information is investigated for the blind measurement of room acoustical parameters. In particular, estimators of room reverberation time (T60) and direct-to-reverberant energy ratio (DRR) are proposed. Short-term temporal dynamic information is obtained from differential (delta) cepstral coefficients. The statistics computed from the zeroth-order delta cepstral sequence serve as input features to a support vector T60 estimator. Long-term temporal dynamic cues, on the other hand, are obtained from an auditory spectrotemporal representation of speech commonly referred to as modulation spectrum. A measure termed as reverberation-to-speech modulation energy ratio, which is computed per modulation frequency band, is proposed and serves as input to T60 and DRR estimators. Experiments show that the proposed estimators outperform a baseline system in scenarios involving reverberant speech with and without the presence of acoustic background noise. Experiments also suggest that estimators of subjective perception of spectral coloration, reverberant tail effect, and overall speech quality can be obtained with an adaptive speech-to-reverberation modulation energy ratio measure.