Spectral subtraction-based filter for experimental modal analysis under harmonics excitation force

In modal analysis, measurement of input force and vibration response are crucial to accurately measure the transfer function of the structure. However, under operating condition, the force induced by operating machinery is impossible to be measured due to the sensor placement issue. In this case, the ambient response induced by the operating force should be suppressed to minimize the error in the Frequency Response Function (FRF) calculation. This paper presents the utilization of a modified spectral subtraction filter for ambient suppression. The introduction of effective ambient magnitude in gain function calculation has increased the efficiency of spectral subtraction filter. This parameter is calculated based on the phase information of the reconstructed artificial ambient response. The measurement using EMA was carried out on a motor-driven structure to verify the proposed technique. Two sets of data under shutdown and running condition were recorded to observe the effect of ambient operating force. Under the operating condition, the measured FRF show the non-identical features at operating frequencies as compared to the baseline data. The utilization of filtering process shows the ambient features contained in the transfer function was effectively suppressed. The output of filtering algorithm could provide an alternative option to perform EMA procedure under running condition.

Wiener Gain and Deep Neural Networks: A Well-Balanced Pair For Speech Enhancement

This paper proposes a Deep Neural Network (DNN)-based Wiener gain estimator for speech enhancement. The proposal is in the framework of the classical spectral-domain speech enhancement algorithms. In this case, we used the Optimal Modified Log-Spectral Amplitude (OMLSA), but consider that this proposal could fit many alternative speech estimation algorithms. We determined the best usage of the DNN approach at learning a robust instance of the Wiener gain estimator according to the characteristics of the SNR estimation and the gain function. To design a DNN architecture adjusted for the speech enhancement task, we study various configuration issues frequently used in DNN-based solutions, including speech representations, residual connections, and causal vs. non-causal designs. Thus, we provide conclusions for the use of DNN architectures with the enhancement purpose. Experiments show that the proposal provides results on the state-of-the-art. But beyond the objective quality measures, there are examples of noisy vs. enhanced speech available for listening to demonstrate in practice the skills of the method in real audio.

Effects of Menstrual Cycles on VOR Gain Functions

Purpose The aim of the present study was to assess the vestibuloocular reflex (VOR) gain function and VOR gain asymmetry during the various phases of the menstrual cycle in young healthy female participants. The study also aimed to characterize the presence or absence of corrective saccades during the various phases of the menstrual cycle. Method Twenty-nine young healthy females participated in the study. The video head impulse test (vHIT) was performed in lateral, left anterior right posterior, and right anterior left posterior plane during the various phases of the menstrual cycle to see the changes in VOR gain function and VOR gain asymmetry ratio changes. Results A repeated measure analysis of variance test did not show any significant main effect for the VOR gain function and VOR gain asymmetry ratio in various phases of the menstrual cycle in all the participants. The result suggested no changes in VOR gain function and VOR asymmetry ratio in healthy females during the menstrual cycle. Also, there was an absence of saccades in the entire participants group during the various phases of the menstrual cycle. Conclusions As the VOR gain function does not change during the various phases of the menstrual cycle in young healthy females, there is no need to consider the various phases of the menstrual cycle while testing any female participant during the vHIT test.

Acoustic Echo Suppression Using Speech Uncertainty In Modulation Domain

<div><div><div><p>Quality degradation of near-end speech in mobile communication or hands free devices is mainly due to acoustic echoes and background noises. The received far-end speech gets reflected from the obstacles present in the surroundings creating acoustic echo. All other disturbances from the near-end environment are considered as background noises. A novel acoustic echo suppression scheme using speech uncertainty in modulation domain (MD) is proposed in this paper. State of the art acoustic echo suppression systems are based on either time domain or frequency domain analysis. In recent times, the modulation domain analysis is popularly used in speech processing, as it captures the human perceptual properties. Modulation domain provides the temporal variation of the acoustic magnitude spectra which acts as an information bearing signal. In this paper, a new method is developed and implemented to model the echo path and estimate the echo in modulation domain. Echo cancellation is done effectively by manipulating the modulation spectrum and employing speech uncertainty. In this method, the microphone input is modelled as a binary hypothesis process and the gain function is modified accordingly. The proposed method shows better performance as compared to other competitive methods for acoustic echo suppression with no audible degradation in the near-end speech. <br></p></div></div></div>

Acoustic Echo Suppression Using Speech Uncertainty In Modulation Domain

<div><div><div><p>Quality degradation of near-end speech in mobile communication or hands free devices is mainly due to acoustic echoes and background noises. The received far-end speech gets reflected from the obstacles present in the surroundings creating acoustic echo. All other disturbances from the near-end environment are considered as background noises. A novel acoustic echo suppression scheme using speech uncertainty in modulation domain (MD) is proposed in this paper. State of the art acoustic echo suppression systems are based on either time domain or frequency domain analysis. In recent times, the modulation domain analysis is popularly used in speech processing, as it captures the human perceptual properties. Modulation domain provides the temporal variation of the acoustic magnitude spectra which acts as an information bearing signal. In this paper, a new method is developed and implemented to model the echo path and estimate the echo in modulation domain. Echo cancellation is done effectively by manipulating the modulation spectrum and employing speech uncertainty. In this method, the microphone input is modelled as a binary hypothesis process and the gain function is modified accordingly. The proposed method shows better performance as compared to other competitive methods for acoustic echo suppression with no audible degradation in the near-end speech. <br></p></div></div></div>

Acoustic Echo Suppression Using Speech Uncertainty In Modulation Domain

<div><div><div><p>Quality degradation of near-end speech in mobile communication or hands free devices is mainly due to acoustic echoes and background noises. The received far-end speech gets reflected from the obstacles present in the surroundings creating acoustic echo. All other disturbances from the near-end environment are considered as background noises. A novel acoustic echo suppression scheme using speech uncertainty in modulation domain (MD) is proposed in this paper. State of the art acoustic echo suppression systems are based on either time domain or frequency domain analysis. In recent times, the modulation domain analysis is popularly used in speech processing, as it captures the human perceptual properties. Modulation domain provides the temporal variation of the acoustic magnitude spectra which acts as an information bearing signal. In this paper, a new method is developed and implemented to model the echo path and estimate the echo in modulation domain. Echo cancellation is done effectively by manipulating the modulation spectrum and employing speech uncertainty. In this method, the microphone input is modelled as a binary hypothesis process and the gain function is modified accordingly. The proposed method shows better performance as compared to other competitive methods for acoustic echo suppression with no audible degradation in the near-end speech. <br></p></div></div></div>

Acoustic Echo Suppression Using Speech Uncertainty In Modulation Domain

<div><div><div><p>Quality degradation of near end speech in mobile communication or hands free devices is mainly due to acoustic echoes and background noises. The received far-end speech gets reflected from the obstacles present in the surroundings creating acoustic echo. All other disturbances from the near end environment are considered as background noises. A novel acoustic echo suppression scheme using speech uncertainty in modulation domain (MD) is proposed in this paper. State of the art acoustic echo suppression systems are based on either time domain or frequency domain analysis. In recent times, the modulation domain analysis is popularly used in speech processing, as it captures the human perceptual properties. Modulation domain provides the temporal variation of the acoustic magnitude spectra which acts as an information bearing signal. In this paper, a new method is developed and implemented to model the echo path and estimate the echo in modulation domain. Echo cancellation is done effectively by manipulating the modulation spectrum and employing speech uncertainty. In this method, the microphone input is modelled as a binary hypothesis process and the gain function is modified accordingly. The proposed method shows better performance as compared to other competitive methods for acoustic echo suppression with no audible degradation in the near end speech.</p><p><br></p></div></div></div>

A critical evaluation of the index of patch quality

The inverse optimality approach can allow us to learn about an animal's environment by assuming their behaviour is optimal. This approach has been applied to animals diving underwater for food to produce the index of patch quality (IPQ), which aims to provide a proxy for prey abundance or quality in a foraging patch based on the animal's diving behaviour. The IPQ has been used in several empirical studies but has never been evaluated theoretically. Here, we discuss the strengths and weaknesses of the IPQ approach from a theoretical angle and review the empirical evidence supporting its use. We highlight several potential issues, in particular with the gain function—the function describing the energetic gain of an animal during a dive—used to calculate the IPQ. We investigate an alternative gain function which is appropriate in some cases, provide a new model based on this function, and discuss differences between the IPQ model and ours. We also find that there is little supporting empirical evidence justifying the general use of the IPQ and suggest future empirical validation methods which could help strengthen the case for the IPQ. Our findings have implications for the field of diving ecology and habitat assessment.