Honey bees are one of the most important insects on the planet since they play a key role in the pollination services of both cultivated and spontaneous flora. Recent years have seen an increase in bee mortality which points out the necessity of intensive beehive monitoring in order to better understand this phenomenon and try to help these important insects. In this scenario, this work presents an algorithm for sound-based classification of honey bee activity reporting a preliminary comparison between various extracted features used separately as input to a convolutional neural network classifier. In particular, the orphaned colony situation has been considered using a dataset acquired in a real situation. Different experiments with different setups have been carried out in order to test the performance of the proposed system, and the results have confirmed its potentiality.

Digital audio equalization is a very common procedure in the acoustic field that allows to improve the listening experience by adjusting the auditory frequency response. The design of graphic equalizers introduces several problems related to the necessity of implementing high performing filters with linear phase, usually characterized by high computational complexity. This paper proposes an innovative linear-phase graphic equalizer based on interpolated finite impulse response (IFIR) filters. IFIR filters seem to be suitable for a graphic equalizer thanks to their properties. In fact, they can reach very narrow transition bands, however with low computational complexity and linear phase, avoiding ripple between adjacent bands. The proposed IFIR equalizer has been compared with some state-of-the-art methods in terms of frequency response, distortion and computational cost. The experimental results have proved the effectiveness of the proposed equalizer, that has shown a considerable reduction on the computational complexity, meanwhile preserving the performances in terms of audio quality.

An open problem in room impulse response (RIR) measurement is the effect of nonlinearities, especially those with memory, present in the measurement system, specifically in the power amplifier and in the loudspeaker. The nonlinearities can corrupt the measurement introducing artifacts. The paper discusses a RIR measurement method that is robust towards these nonlinearities. The proposed methodology allows measuring the RIR using the cross-correlation method, i.e., computing the cross-correlation between the output signal and an appropriate sequence. In contrast to other cross-correlation based methods, the proposed approach directly estimates the first-order kernel of the Volterra filter modeling the measurement systems, i.e., the system impulse response for small signals. The proposed approach exploits the concepts of orthogonal periodic sequences, recently proposed in the literature. The input signal can be any periodic persistently exciting sequence and can also be a quantized sequence. Measurements performed both on an emulated scenario and in real environments illustrate the validity of the approach and compare it with other competing RIR measurement methods.

The paper introduces a novel family of deterministic signals, the orthogonal periodic sequences (OPSs), for the identification of functional link polynomial (FLiP) filters. The novel sequences share many of the characteristics of the perfect periodic sequences (PPSs). As the PPSs, they allow the perfect identification of a FLiP filter on a finite time interval with the cross-correlation method. In contrast to the PPSs, OPSs can identify also non-orthogonal FLiP filters, as the Volterra filters. With OPSs, the input sequence can have any persistently exciting distribution and can also be a quantized sequence. OPSs can often identify FLiP filters with a sequence period and a computational complexity much smaller than that of PPSs. Several results are reported to show the effectiveness of the proposed sequences identifying a real nonlinear audio system.

The absence of the queen in a beehive is a very strong indicator of the need for beekeeper intervention. Manually searching for the queen is an arduous recurrent task for beekeepers that disrupts the normal life cycle of the beehive and can be a source of stress for bees. Sound is an indicator for signalling different states of the beehive, including the absence of the queen bee. In this work, we apply machine learning methods to automatically recognise different states in a beehive using audio as input. We investigate both support vector machines and convolutional neural networks for beehive state recognition, using audio data of beehives collected from the NU-Hive project. Results indicate the potential of machine learning methods as well as the challenges of generalizing the system to new hives.

Compression driver design involves the study of complex mathematical models characterized by a great number of variables, implying high computational cost and long design time. Therefore, an optimization procedure is required to enhance the design procedure, especially from the parameters point of view. In this paper, a combined approach based both on evolution strategy procedure and neural network model is presented. Taking into consideration several tests on a real compression driver, the proposed method is capable to enhance the design procedure from the point of view of obtained frequency response and of the computational performance.

Multichannel acoustic echo cancellers aim at reducing the undesired acoustic coupling among microphones and loudspeakers in multichannel audio/video teleconferencing systems. In this scenario, double-talk refers to the situation in which there is an active speaker both in the remote room and in the local room. The detection of double-talk is one of the main issues to be faced in such systems to ensure a correct echo cancellation. Indeed, filters coefficients update has to be suppressed during double-talk in order to prevent the filter from diverging because of the presence of the local speaker. In this paper, a novel approach for double-talk detection is discussed based on the estimation of the fundamental frequency of the residual error signals through adaptive second-order notch filters. More specifically, simultaneous speaker activity in the remote and local rooms is revealed by exploiting the same frequency tracking introduced for multichannel decorrelation. Several experiments have been carried out to prove the effectiveness of the proposed approach also making comparison with other solutions of the state of the art.

The paper proposes a novel approach for measuring the room impulse response that is robust toward the nonlinearities affecting the power amplifier or the loudspeaker. The approach is implemented by modeling the acoustic path as a Legendre nonlinear filter and by measuring the first-order kernel using perfect periodic sequences and the cross-correlation method. Perfect sequences for Legendre filters are periodic sequences that guarantee the orthogonality of the Legendre basis functions over a period. They ensure the robustness of the first kernel measurement toward nonlinear distortions. The paper also explains how perfect periodic sequences for Legendre filters that are suitable for room impulse response identification can be developed. Experimental results involving both simulated and real environments illustrate the effectiveness and the robustness of the proposed approach.

Acoustic echo cancellers are used in teleconferencing systems in order to reduce undesired echoes due to coupling between microphones and loudspeakers. Stereophonic systems provide more realistic experience than single-channel systems, since listeners have spatial information that helps to identify the speaker position. Assuming this scenario, a suitable choice for the system parameters becomes essential to improve the audio reproduction quality. Error-driven optimization strategies are usually used to obtain an optimal system configuration but there is no relationship with the quality desired by the user. In this paper, an interactive evolutionary algorithm is adopted for a stereophonic acoustic echo cancellation system in order to meet subjective specifications in the optimization stage. In this way, the optimal system configuration is derived according to a user-driven approach in order to satisfy the quality requirements demanded by users availing such stereophonic systems. Experimental results prove the effectiveness of the proposed interactive architecture according to both objective and subjective measures.

In the field of immersive audio, crosstalk cancellation is adopted preserving the spatial characteristics of the reproduced signals. It is based on the use of HRTFs that can be approximated through a free-field model. However, this method assumes that the physical head is removed and replaced with two monopole receivers at the position of the ears and thus the source characteristics is not considered. In this context, a new approximation for the HRTFs is introduced taking into account the source directivity, i.e., the loudspeaker is modelled as a rigid sphere with a membrane vibrating on a spherical cap. A deep investigation on the effect of introducing the source directivity in the free-field model is reported in this paper. In particular, several experimental results are shown, considering both objective and subjective measurements, to validate the effectiveness of the proposed solution in terms of both channel separation and audio quality preservation.

Voice activity detection algorithms are intended to discriminate vocal segments from silence or other background noise periods. This is an important aspect in many speech communication systems and applications, e.g. teleconferencing systems. Therefore, a new method for detecting voiced segments in a multichannel scenario is proposed in this work by exploiting the fundamental frequency tracking through adaptive notch filters previously introduced for interchannel coherence reduction in multichannel acoustic echo cancellation systems. Novel expedients are presented in this paper for obtaining a more accurate tracking and thus for guaranteeing a correct voiced/unvoiced decision. The great advantage of the presented solution is related to the possibility of deriving a self-contained solution for multichannel acoustic echo cancellation where all the involved algorithms are based on the same fundamental frequency estimation. Experimental results prove the effectiveness of the proposed approach in correctly identifying vocal segments and silence and background noise periods.

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.

This paper introduces a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. Their basis functions are polynomials, specifically, products of Legendre polynomial expansions of the input signal samples. Legendre nonlinear filters share many of the properties of the recently introduced classes of Fourier nonlinear filters and even mirror Fourier nonlinear filters, which are based on trigonometric basis functions. In fact, Legendre nonlinear filters are universal approximators for causal, time invariant, finite-memory, continuous, nonlinear systems and their basis functions are mutually orthogonal for white uniform input signals. In adaptive applications, gradient descent algorithms with fast convergence speed and efficient nonlinear system identification algorithms can be devised. Experimental results, showing the potentialities of Legendre nonlinear filters in comparison with other linear-in-the-parameters nonlinear filters, are presented and commented.

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.

The paper deals with the development of a real time system for the reproduction of an immersive audio field considering the crosstalk cancellation and the room response equalization issues. In particular, the real-time system is composed of two parts: a crosstalk cancellation network and a combined multipoint equalization structure. The former is required in order to have a spatialized audio and it is based on the free-field relationship in order to not introduce a timbre alteration. The latter is used to improve the objective and subjective quality of sound reproduction systems by compensating the room and loudspeakers transfer function. Both steps are based on a-priori analysis of the real environment using real impulse responses measured in different positions. In particular, an offline procedure capable of determining the tuning parameters for the crosstalk network and of deriving the final filters for the equalization structure, is adopted. Several results are presented in order to show the effectiveness of the proposed algorithms considering objective and subjective evaluations and comparing the presented approach with the state of the art.

Nowadays, there is a large interest towards multimedia audio systems as a consequence of the development of advanced digital signal processing techniques. In particular, immersive speech communication system has gaining increasing attention since they allow to reproduce realistic acoustic image, and thus achieving good performance in terms of sound quality and accuracy. In this scenario a fundamental role is played by intelligent acoustic interfaces which aim at acquiring audio information, processing it, and returning the processed information to the audio rendering system. In this paper, an effective intelligent acoustic interface composed of a microphone array and a signal processing system capable to enhance the intelligibility of the desired information of the transmitting room is proposed, combined with an advanced reproduction system based on an efficient application of a wave field synthesis technique capable to reproduce an immersive scenario in the receiving room. The whole system has been assessed within a speech communication application involving a moving desired source in a real scenario: objective and subjective evaluation has been reported in order to show the overall system performance.

Reverberation is a well known effect that has an important role in our listening experience. A great deal of research has been devoted in the last decades aiming to artificially reproduce the reverberation effect exploiting a hybrid reverberation structure. In this context, several automatic procedures have been presented in the literature in order to derive the reverberator structure considering the mixing time evaluation and the minimization functions definition for the late reverberation device. Taking into consideration these aspects, a deep analysis of hybrid digital reverberator audio quality is here proposed, introducing a new parameter for the definition of the mixing time and two new cost functions for the definition of the late reverberation parameters. More in detail, starting from the considerations derived from a previous accurate approach based on the mel frequency cepstral coefficients, the new cost functions are based on the evaluation of the perceptual linear predictive and power normalized cepstral coefficients. Several results are reported, in terms of objective measure, performance analysis and subjective measures, taking into consideration different real impulse responses and various input stimuli and making a comparison with the state of the art. In particular, the obtained results show that a good accuracy can be achieved also considering a low number of coefficients, therefore improving the computational performance.

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.

This paper deals with methods for multiple position room response equalization. Differently from a well-known technique working in the time domain and based on fuzzyc-means clustering, in the proposed approach most of the operations are performed in the frequency domain and, in particular, the fuzzyc-means clustering is applied to the room magnitude responses at different positions. It is shown that working in the frequency domain allows us to obtain equalization performances at least similar to those of the time domain approach with a strongly reduced computational complexity. In addition, different techniques that can replace the fuzzyc-means clustering algorithm in the derivation of the prototype room response equalizer, with additional reduction of the number of operations, are discussed. Finally, the results of three sets of experiments are used to illustrate the performance, the robustness and the quality of the proposed room response equalization method using alternative prototype design strategies applied to different environments.

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.

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.

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.