Laura Romoli

A Mixed Decorrelation Approach for Stereo Acoustic Echo Cancellation Based on the Estimation of the Fundamental Frequency

In teleconferencing systems, undesired echoes due to coupling between the loudspeaker and the microphone can be reduced using acoustic echo cancellers (AECs). In order to introduce better performance in terms of sound localization, at least stereophonic AECs (SAECs) have to be employed. In this case, the correlation between the two channels prevents a correct identification of the echo paths and a signal decorrelation is needed. In this paper, a novel mixed approach to signal decorrelation is proposed based on the estimation of the fundamental frequency. The principle of the proposed structure is to use an approach based on the “missing-fundamental” phenomenon at low frequencies (below 500 Hz), a time-varying all-pass filter controlled by the fundamental frequency at medium and high frequencies, and a time-varying multi-notch filter for improving performance in the upper part of the spectrum. Experiments confirm the effectiveness of the proposed approach in terms of correct identification of the echo paths and stereo perception preservation.

A Combined Psychoacoustic Approach for Stereo Acoustic Echo Cancellation

Acoustic echo cancelers (AECs) are used in teleconferencing systems to reduce undesired echoes originating from coupling between the loudspeaker and the microphone. Better performance in terms of sound localization can be achieved only by using multichannel AECs. By the use of a two-channel (stereo) system, it is already possible to obtain more realistic performance than the monochannel case because listeners have more spatial information that helps to identify the speaker position. In this paper, a novel approach to stereo AEC is proposed based on a combination of psychoacoustic effects. The principle of the proposed structure is to use an approach based on the “missing-fundamental” phenomenon at low frequencies (below 500 Hz) and a modified phase modulation approach at higher frequencies. Several results are presented in terms of magnitude-squared coherence, Itakura-Saito measure, convergence speed of adaptive filters, interaural cross-correlation, and subjective evaluation, in order to confirm the validity of the proposed approach.

Legendre nonlinear filters

The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. The novel sub-class combines the best characteristics of truncated Volterra filters and of the recently introduced even mirror Fourier nonlinear filters, in particular: (i) Legendre nonlinear filters can arbitrarily well approximate any causal, time-invariant, finite-memory, continuous, nonlinear system; (ii) their basis functions are polynomials, specifically, products of Legendre polynomial expansions of the input signal samples; (iii) the basis functions are also mutually orthogonal for white uniform input signals and thus, in adaptive applications, gradient descent algorithms with fast convergence speed can be devised; (iv) perfect periodic sequences can be developed for the identification of Legendre nonlinear filters. A periodic sequence is perfect for a certain nonlinear filter if all cross-correlations between two different basis functions, estimated over a period, are zero. Using perfect periodic sequences as input signals permits the identification of the most relevant basis functions of an unknown nonlinear system by means of the cross-correlation method. Experimental results involving identification of real nonlinear systems illustrate the effectiveness and efficiency of this approach and the potentialities of Legendre nonlinear filters. HighlightsThe paper discusses Legendre nonlinear (LN) filters.LN filters arbitrarily well approximate any finite-memory continuous nonlinear system.The basis functions are mutually orthogonal polynomials for white uniform inputs.Perfect periodic sequences (PPSs) can be developed for their identification.PPSs permit us to identify unknown systems by means of the cross-correlation method.

A novel approach to channel decorrelation for stereo Acoustic Echo Cancellation based on missing fundamental theory

Decorrelation is a well known issue in the context of Stereophonic Acoustic Echo Cancellation: it is related to the problem of uniquely identifying each pair of room acoustic paths, due to high inter-channel coherence. In this paper, a novel approach to decorrelate a stereo signal based on the missing fundamental phenomenon is proposed. An adaptive algorithm is employed to track the behavior of one of the two channels, ensuring a continuous decorrelation without affecting the stereo quality. Several results are presented comparing our approach with Masked Noise injection method in terms of Magnitude Square Coherence, Itakura Saito measure and Convergence Speed of adaptive filters in order to confirm the validity of the proposed approach.

A novel decorrelation approach for multichannel system identification

Multichannel sound reproduction systems aim at providing an optimal acoustical sensation to the listener by enhancing the listening experience and improving the spatial sound impression of the virtual scene. In this context, many audio applications requiring adaptive processing schemes have been developed in order to improve the performance of the audio reproduction. However, online multichannel systems identification requires the introduction of suitable solutions for overcoming the well-known non-uniqueness problem related to the correlation existing among the loudspeaker signals. This issue has been deeply investigated considering stereophonic systems but its extension to multichannel systems may not be so straightforward. In this paper, a novel solution for speech and audio signals is presented based on the “missing-fundamental” phenomenon. Experimental results proved the effectiveness of the approach also making comparisons with the existing state of the art.

Identification of Hammerstein model using cubic splines and FIR filtering

Nonlinear models are exploited in the field of digital audio systems for modelling most of real-world devices that show a nonlinear behaviour. Among nonlinear models, Hammerstein systems are realized through a static nonlinearity cascaded with a linear filter. In this paper, the Hammerstein coefficients are estimated using an adaptive Catmull-Rom cubic spline for the static nonlinearity and an adaptive FIR filter for the dynamic linear system also introducing a preprocessing for the time delay estimation. Experimental results confirm the effectiveness of the proposed approach, making also comparisons with existing techniques of the state of the art.

A Combined Approach for Channel Decorrelation in Stereo Acoustic Echo Cancellation Exploiting Time-Varying Frequency Shifting

Multichannel acoustic echo cancellers are used in teleconferencing systems in order to reduce undesired echoes and to introduce better performance in terms of sound localization in the presence of more than one participant. Already stereophonic systems obtain realistic performance, since listeners have spatial information that helps to identify the speaker position. Unfortunately, the correlation between the two channels prevents a correct identification of the echo paths and signal decorrelation is needed. In this letter, a decorrelation approach is proposed, combining the missing-fundamental theory with frequency shifting. Therefore, the proposed approach is based on the computation of an adaptive parameter related to the fundamental frequency that is also used for controlling the desired frequency shift value. Experiments confirm that high performance in terms of magnitude squared coherence reduction and convergence speed increase can be obtained, also comparing it with other approaches of the state of the art and outperforming previous results.

Adaptive Feedback Active Noise Control for Yacht Environments

In a yacht cabin, high-quality absorbing materials can reduce in a good way medium and high-frequency noises, but they are completely inefficient in the case of low-frequency noises. In this brief, a detailed analysis of low-frequency noises in a yacht environment is presented; several boat conditions, depending on the presence of different noise sources (e.g., air conditioning, engines) and various navigation velocities are investigated. In this context, a specific multichannel feedback active noise control system, derived from the well-known filtered-x approach, is designed and installed in a bedroom of a yacht in order to reduce the acoustical annoyance using four error microphones and two sub-woofers for antinoise generation. The results of practical experiments are shown in order to demonstrate the effectiveness of the proposed system.

A multichannel and multiple position adaptive room response equalizer in warped domain

An adaptive multichannel and multiple position room response equalization system is proposed. The room responses are adaptively estimated with good accuracy by reducing the interchannel coherence with a technique based on the missing fundamental phenomenon, that introduces only a mild alteration of the sound timbre. The equalizer is designed in warp frequency domain for improving equalization in the low frequency region, reducing the computational cost of the design and deriving an algorithm capable to work in real time. Simulation results using signals acquired in a real environment illustrate the effectiveness of the proposed approach.

Intelligent Acoustic Interfaces With Multisensor Acquisition for Immersive Reproduction

Immersive speech communication systems have been gaining increasing attention due to their ability to reproduce enhanced acoustic images, and thus achieving good performance in terms of sound quality and accuracy. In this context , a fundamental role is played by intelligent acoustic interfaces (IAIs), which aim at acquiring and/or reproducing desired acoustic information with enhanced perception. The recent widespread availability of multimedia devices, equipped with different kind of sensors, has broadened the range of data processing methods, thus giving a chance for developing advanced IAIs. In this paper, we propose an immersive communication system composed of two IAIs: the first one exploits microphones and cameras, together with a signal processing system, to reduce unwanted noise and enhance the speech quality of the desired information in the transmitting room; the second one is an advanced reproduction system based on a loudspeaker array and on an effective wave field synthesis technique capable of reproducing the spatial perception of the desired speech source in the receiving room. The whole system has been assessed in simulated and real immersive communication scenarios: objective and subjective evaluations have been shown the effectiveness of the proposed system.