Acoustic Communication Research Articles

Modulation recognition for underwater acoustic communication based on hybrid neural network and feature fusion

It is a huge challenge for underwater acoustic receivers to correctly identify modulation methods due to the complex underwater channel environment and severe noise interference. Combined with the lightweight network (SqueezeNet) and attention mechanism (SENet), a multi-attribute and multi-scale feature fusion model based on a hybrid neural network is proposed, which achieves efficient and accurate recognition for modulation modes. First, the wavelet time-frequency (WTF) spectrum, square power spectrum, and contour maps of cyclic spectrum are extracted as multi-attribute inputs for the network to reduce the impact of inherent defects in single attribute feature. Second, shallow and deep features based on the SqueezeNet model are obtained as multi-scale features, of which the key feature expression ability is enhanced by the SENet model to provide sufficient feature information for modulation recognition. The simulation experiments and sea trial data confirm that the suggested method demonstrates strong generalization capabilities and effectiveness when applied to underwater acoustic channels and environmental noise. In contrast to algorithms in existence, the method verifies superior recognition abilities.

Time and place affect the acoustic structure of frog advertisement calls

Abstract Acoustic communication signals are important for species recognition and mate attraction across numerous taxa. For instance, most of the thousands of species of frogs have a species-specific advertisement call that females use to localize and discriminate among potential mates. Thus, the acoustic structure of the advertisement call is critical for reproductive success. The acoustic structure of calls will generally diverge over evolutionary time and can be influenced by the calls of sympatric species. While many studies have shown the influence of geography on contemporary call variation in populations of frogs, no study has compared the acoustic structure of frog calls across many species to ask whether we can detect an influence of divergence time and overall geographic overlap on the differences in acoustic structure of species-typical calls that we observe now. To this end, we compared acoustic features of the calls of 225 species of frogs within 4 families. Furthermore, we used a behavioral assay from 1 species of frog to determine which acoustic features to prioritize in our large-scale analyses. We found evidence that both phylogeny (time) and geography (place) relate to advertisement call acoustics albeit with large variation in these relationships across the 4 families in the analysis. Overall, these results suggest that, despite the many ecological and evolutionary forces that influence call structure, the broad forces of time and place can shape aspects of advertisement call acoustics.

Acoustic Communication in Dendroctonus adjunctus Blandford (Curculionidae Scolytinae): Description of Calls and Sound Production Mechanism.

The acoustic communication system (ACS) in bark beetles has been studied mainly in species of the genera Dendroctonus, Ips and Polygraphus. Specifically, ACS of the roundheaded pine beetle, Dendroctonus adjunctus, has been little studied. In this study, we described the stridulatory apparatus of this beetle using optical and scanning electron microscopy and recorded the call types produced by males in three behavioral contexts: stress, female-male-, and male-male interactions. From the spectrograms and waveforms, call types, as well as temporal (tooth strike, tooth strike rate, and intertooth strike interval) and spectral features (minimum, maximum and dominant frequency), were determined. Males have a functional elytro-tergal stridulatory apparatus-females do not-consisting of a file for the pars stridens and two lobes for the plectrum. Most of spectro-temporal features were statistically different between single- and multi-noted calls and across the three behavioral contexts. In the male-male interaction, a new type of call named "withdrawal" was produced by the male withdrawing or fleeing. Our results suggest that the spectro-temporal features of single- and multiple-noted calls in the three behavioral conditions are specific and different from each other. Yet, the combination of single and multiple calls determines an overall calling pattern characteristic of the tested behaviors and, therefore, is species-specific.

Amplitude‐Phase Dual‐Channel Encrypted Acoustic Meta‐Holograms

AbstractEncrypted acoustic meta‐holograms have potential applications in confidential acoustic information communication, noise control, acoustic cloaking, acoustic illusion, etc. Conventional encrypted optical and acoustic meta‐holograms only focus on the encrypted hologram in a single channel, viz. modulating spatial amplitude to project a holographic image. Here, the concept of an amplitude‐phase dual‐channel encrypted acoustic meta‐hologram (DrEAM) is proposed, capable of generating, encrypting, and decrypting both amplitude and phase holographic images. This unique concept of “phase holographic image” introduces a new degree of freedom for meta‐holograms, leading to dual‐channel encrypted acoustic holography. Acoustic metasurface with simultaneous amplitude and phase modulations is employed to realize this dual‐channel encryption. The findings may offer the possibility to increase the capacity of the encrypted acoustic meta‐holograms, which can lead to practical applications in, for example, multi‐channel acoustic field communications, complex noise control, and acoustic illusions.

The response of sea turtles to vocalizations opens new perspectives to reduce their bycatch

Incidental capture of non-target species poses a pervasive threat to many marine species, with sometimes devastating consequences for both fisheries and conservation efforts. Because of the well-known importance of vocalizations in cetaceans, acoustic deterrents have been extensively used for these species. In contrast, acoustic communication for sea turtles has been considered negligible, and this question has been largely unexplored. Addressing this challenge therefore requires a comprehensive understanding of sea turtles’ responses to sensory signals. In this study, we scrutinized the avenue of auditory cues, specifically the natural sounds produced by green turtles (Chelonia mydas) in Martinique, as a potential tool to reduce bycatch. We recorded 10 sounds produced by green turtles and identified those that appear to correspond to alerts, flight or social contact between individuals. Subsequently, these turtle sounds—as well synthetic and natural (earthquake) sounds—were presented to turtles in known foraging areas to assess the behavioral response of green turtles to these sounds. Our data highlighted that the playback of sounds produced by sea turtles was associated with alert or increased the vigilance of individuals. This therefore suggests novel opportunities for using sea turtle sounds to deter them from fishing gear or other potentially harmful areas, and highlights the potential of our research to improve sea turtles populations’ conservation.

Modulation recognition of underwater acoustic communication signals based on neural architecture search

Modulation recognition of underwater communication signals is a critical aspect of underwater information confrontation. However, the current deep learning-based methods for underwater communication modulation recognition often mimic neural network architectures used in image processing and speech processing, tending to perform poorly in low signal-to-noise ratio (SNR) conditions. This paper introduces a novel approach by utilizing neural architecture search (NAS) method. By automatically searching for neural architectures that are well-suited for modulation recognition in underwater environment, our proposed method improves the classification performance particularly in low SNR conditions. Furthermore, we have also proposed a recognition method based on attention mechanism and feature fusion, which substantially enhances the accuracy of identifying phase-modulated signals. Numerical simulation and experimental data are used to demonstrate performance of proposed methods.

Emotional vocalizations alter behaviors and neurochemical release into the amygdala

The basolateral amygdala (BLA), a brain center of emotional expression, contributes to acoustic communication by first interpreting the meaning of social sounds in the context of the listener’s internal state, then organizing the appropriate behavioral responses. We propose that modulatory neurochemicals such as acetylcholine (ACh) and dopamine (DA) provide internal-state signals to the BLA while an animal listens to social vocalizations. We tested this in a vocal playback experiment utilizing highly affective vocal sequences associated with either mating or restraint, then sampled and analyzed fluids within the BLA for a broad range of neurochemicals and observed behavioral responses of adult male and female mice. In male mice, playback of restraint vocalizations increased ACh release and usually decreased DA release, while playback of mating sequences evoked the opposite neurochemical release patterns. In non-estrus female mice, patterns of ACh and DA release with mating playback were similar to males. Estrus females, however, showed increased ACh, associated with vigilance, as well as increased DA, associated with reward-seeking. Experimental groups that showed increased ACh release also showed the largest increases in an aversive behavior. These neurochemical release patterns and several behavioral responses depended on a single prior experience with the mating and restraint behaviors. Our results support a model in which ACh and DA provide contextual information to sound analyzing BLA neurons that modulate their output to downstream brain regions controlling behavioral responses to social vocalizations.

Emotional vocalizations alter behaviors and neurochemical release into the amygdala.

The basolateral amygdala (BLA), a brain center of emotional expression, contributes to acoustic communication by first interpreting the meaning of social sounds in the context of the listener's internal state, then organizing the appropriate behavioral responses. We propose that modulatory neurochemicals such as acetylcholine (ACh) and dopamine (DA) provide internal-state signals to the BLA while an animal listens to social vocalizations. We tested this in a vocal playback experiment utilizing highly affective vocal sequences associated with either mating or restraint, then sampled and analyzed fluids within the BLA for a broad range of neurochemicals and observed behavioral responses of adult male and female mice. In male mice, playback of restraint vocalizations increased ACh release and usually decreased DA release, while playback of mating sequences evoked the opposite neurochemical release patterns. In non-estrus female mice, patterns of ACh and DA release with mating playback were similar to males. Estrus females, however, showed increased ACh, associated with vigilance, as well as increased DA, associated with reward-seeking. Experimental groups that showed increased ACh release also showed the largest increases in an aversive behavior. These neurochemical release patterns and several behavioral responses depended on a single prior experience with the mating and restraint behaviors. Our results support a model in which ACh and DA provide contextual information to sound analyzing BLA neurons that modulate their output to downstream brain regions controlling behavioral responses to social vocalizations.

Delay-aware and reliable medium access control protocols for UWSNs: Features, protocols, and classification

Underwater Wireless Sensor Networks (UWSNs) are garnering significant interest for their broad potential in critical applications, including environmental monitoring, resource exploration, and disaster prevention. These networks, however, face unique challenges due to the complexities of underwater acoustic communication, such as extended propagation delays and environmental disturbances. These issues necessitate the development of sophisticated Medium Access Control (MAC) protocols specifically designed for UWSNs, distinct from those used in Terrestrial Wireless Sensor Networks (TWSNs). This paper provides a comprehensive review of MAC protocols tailored for various task-oriented scenarios in UWSNs, beginning with an in-depth exploration of the challenges specific to designing MAC protocols for these networks. The discussion emphasizes the importance of minimizing transmission latency and maximizing reliability, crucial for effective application-specific operations. This survey categorizes existing protocols based on these critical performance metrics, while also addressing the imperative of energy efficiency. Furthermore, it details the adaptive strategies these protocols employ to cope with the dynamic and challenging underwater acoustic channels. In addition to presenting a comparative analysis of the protocols, this work identifies pressing research gaps and poses open questions, establishing itself as an indispensable resource for researchers seeking to advance the field of MAC protocols in UWSNs.

MDF-Net: A multi-view dual-attention fusion network for efficient bird sound classification

Bird sound serves as a crucial means of acoustic communication for birds, and its classification research is conducive to the protection, health, and diversity of the ecological ecosystems. Using various feature extraction methods to extract multi-view features can provide more comprehensive information about bird sound, which is a potential method to improve the accuracy of bird sound classification. However, efficiently fusing multi-view features to identify birds accurately remains a challenging task. To address this problem, this paper presents an efficient bird sound classification framework called MDF-Net. The approach extracts four acoustic features from bird sound audios, including wavelet transform spectrogram, Hilbert-Huang transform spectrogram, short-time Fourier transform spectrogram, and Mel-frequency cepstral coefficients, to fully describe the characteristics of bird sound from different views. Subsequently, convolutional neural network is used as advanced feature extractor to obtain deep features of these spectrograms. Then, the multi-head self-attention mechanism focuses on the correlation and importance of different features in each view to obtain essential and expressive feature representations. And the cross-attention mechanism is employed to align and correlate information in the four views, which makes it easier for the classifier to understand the relationships between features of different views. Finally, combined with the results of the dual-attention mechanism, a multi-view fusion feature with difference and diversity is constructed, and it applied to the bird sound classification. In this study, audios from16 bird species constitute the dataset. The multi-view fusion feature based on MDF-Net achieved a classification accuracy of 97.29%, outperformed the 9 single features and 3 fused features used in the experiments. The result demonstrate that the proposed MDF-Net successfully captures the feature relationships within single-view and between multi-view, providing crucial information for correctly classifying bird sound samples. The approach efficiently fuses the features of different views and improves the performance of bird sound classification.

Direction of Arrival Joint Prediction of Underwater Acoustic Communication Signals Using Faster R-CNN and Frequency–Azimuth Spectrum

Utilizing hydrophone arrays for detecting underwater acoustic communication (UWAC) signals leverages spatial information to enhance detection efficiency and expand the perceptual range. This study redefines the task of UWAC signal detection as an object detection problem within the frequency–azimuth (FRAZ) spectrum. Employing Faster R-CNN as a signal detector, the proposed method facilitates the joint prediction of UWAC signals, including estimates of the number of sources, modulation type, frequency band, and direction of arrival (DOA). The proposed method extracts precise frequency and DOA features of the signals without requiring prior knowledge of the number of signals or frequency bands. Instead, it extracts these features jointly during training and applies them to perform joint predictions during testing. Numerical studies demonstrate that the proposed method consistently outperforms existing techniques across all signal-to-noise ratios (SNRs), particularly excelling in low SNRs. It achieves a detection F1 score of 0.96 at an SNR of −15 dB. We further verified its performance under varying modulation types, numbers of sources, grating lobe interference, strong signal interference, and array structure parameters. Furthermore, the practicality and robustness of our approach were evaluated in lake-based UWAC experiments, and the model trained solely on simulated signals performed competitively in the trials.

Enriched social environment affects the utterance of acoustic signals of captive François' langurs

Vocal communication serves as an important mode of interaction among animals. The quantitative analysis of acoustic signals holds scientific value in highlighting the importance of understanding the social-ecological contexts and their effects on acoustic communication. The results can provide a direct scientific guidance for enhancing the welfare and management of captive animals. From January to February 2022 and from December 2022 to February 2023, we conducted a study involving 30 captive François' langurs (Trachypithecus francoisi) housed in nine enclosures. We collected acoustic signals along with their associated social-ecological contexts and recorded the social composition and number of François' langurs in each enclosure. We in total identified 23 call types based on human ear auditory, spectrogram visual inspection, and quantitative analysis of 37 acoustic parameters. Our findings revealed that adult males exhibited nine call types (five adult male-specific types), adult females 11 call types (seven adult female-specific types), juveniles eight call types (two juvenile-specific types), and infants five call types (two infant-specific types). The asymmetry in call types indicated distinct social roles among different sex-age classes of François' langurs. We found that a complex social composition or larger group size resulted in a more diverse range of call types and increased utterance frequency among François' langurs. The increased utterance frequency was linked to calls used in neutral (contact), affiliation, mating, and vigilance contexts, indicating that a diverse social setting encourages social interaction and boosts the occurrence of natural behaviors, and may also result in increased tension and anxiety. Implementing a one-male multi-female model with ample breeding space for captive François' langurs was identified as beneficial for enhancing vocal communication and improving animal welfare. This study established the first vocal repertoire of François' langurs, offering a novel scientific approach to evaluating the welfare of this endangered species through vocal behaviors.

Improving the efficiency of channel evaluation during high-speed data transmission in underwater acoustic communication with OFDM

Problem statement. The organization of noise-resistant wireless underwater acoustic communication is not a simple and solved task. One of the main problems is the multipath propagation of a sound acoustic wave as a result of re–reflections from the seabed surface and a change in the frequency of signal vibrations when the receiver and transmitter move relative to each other. Thus, finding a channel evaluation solution that can improve the quality of communication is an urgent task for developers of underwater acoustic communication systems. Purpose. To consider the possibility of developing effective methods for processing underwater acoustic communication signals with high noise immunity by evaluating the communication channel. Results. The possibility of using an adaptive filter with a sliding window to evaluate the channel during high-speed data transmission in underwater acoustic communication is shown. The simulation results showed that the proposed adaptive filter with a sliding window surpasses the normalized adaptive filters in terms of the BER bit error and wins over additive filters with an exponential window in reducing the number of mathematical operations. When modeling wireless acoustic communication systems with OFDM, error-free data transmission with a spectral efficiency of 0.33 bits/s/Hz was achieved. Practical significance. The obtained results can be used to improve the wireless transmission of data in underwater acoustic communication due to the proposed algorithm of the adaptive filter.

Body size and sequence of host colonisation predict the presence of acoustic signalling in beetles

Acoustic communication is widespread in beetles, is often sexually dimorphic, and plays a significant role in behaviours such as premating recognition, courtship, and copulation. However, the factors that determine the presence or absence of acoustic signalling in a given species remain unclear. We examined acoustic communication in bark beetles (Scolytinae) and pinhole borers (Platypodinae), which are two speciose groups with widespread sound production capabilities. We show that body size along with the sequence of host colonisation predict the presence of acoustic communication, and report, for the first time in the animal kingdom, a size limit—1.9 mm—below which acoustic signalling ceases to be present.

A Throughput Performance Analysis Method for Multimode Underwater Acoustic Communication Network Based on Markov Decision Process

The multimode underwater acoustic communication network is a novel form of underwater acoustic communication that adjusts its communication mode to enhance overall performance. Current performance analysis methods are primarily applied to single-mode networks and assume uniform communication capability across all nodes, making them unsuitable for multimode networks. This paper investigates the multimode communication of the physical layer, considering factors such as the marine environment, the node transmitting sound source level, and the transmitting distance. A decoding conflict model is proposed to support multimode concurrent transmission scenarios. The communication mode is designed to be compatible with the channel and node characteristics. Additionally, using a Markov decision process, this paper establishes a performance evaluation and analysis model for multimode underwater acoustic networks to determine throughput performance limits in real underwater environments. Simulations across various scenarios validate that the throughput performance limits obtained by this method are more accurate under multimode networks, with an improvement in accuracy of over 67.5% compared to existing methods.

Context-driven communication during deep-sea foraging in a social toothed whale.

Social deep-diving odontocetes face the challenge of balancing near-surface proximity to oxygen and group members with foraging in the deep sea. Individuals rely on conspecifics for critical life functions, such as predator defence, but disperse during foraging to feed individually. To understand the role of social acoustic mediation during foraging in deep-diving toothed whales, we investigated the context of social burst-pulse call production in Risso's dolphin (Grampus griseus) using biologgers. Dolphins produced context-specific burst pulses predominantly during daytime foraging, preceding or following foraging dives and in the early descent of daytime deep dives. Individuals applied differential short and long burst-pulse calls intended for either near-surface receivers (horizontal transmission) or deep-foraging receivers (vertical transmission). Our results show that deep-diving toothed whales are reliant on acoustic communication during certain foraging contexts, to relay information including foraging conditions or an individual's location. Moreover, they accentuate the importance of maintaining acoustic contact with conspecifics, specifically when dispersed during deeper foraging. It also signifies that our oceanic top predators may be specifically vulnerable to the current strong increase in anthropogenic noise. Potential masking of the signals from group members communicating at a distance could undermine their social cohesion, and hence their capacity to maintain vital life functions.

Health monitoring and image restoration for a human in under water using acoustic communication

Health monitoring and image restoration for a human in under water using acoustic communication

A metric to quantify the time-varying characteristics of underwater acoustic communication channels.

Underwater acoustic communication signals suffer from time dispersion due to time-varying multipath propagation in the ocean. This leads to intersymbol interference, which in turn degrades the performance of the communication system. Typically, the channel correlation functions are employed to describe these characteristics. In this paper, a metric called the channel average correlation coefficient (CACC) is proposed from the correlation function to quantify the time-varying characteristics. It has a theoretical negative relationship with communication performance. Comparative analysis involving simulations and experimental data processing highlights the superior effectiveness of CACC over the traditional metric, the channel coherence time.

ECR Spotlight – Mathilde Martin

ECR Spotlight is a series of interviews with early-career authors from a selection of papers published in Journal of Experimental Biology and aims to promote not only the diversity of early-career researchers (ECRs) working in experimental biology but also the huge variety of animals and physiological systems that are essential for the ‘comparative’ approach. Mathilde Martin is an author on ‘ Use of acoustic signals in Cape fur seal mother–pup reunions: individual signature, signal propagation and pup home range’, published in JEB. Mathilde conducted the research described in this article while a PhD student in Dr Isabelle Charrier's lab at the Institute of Neurosciences Paris-Saclay (NeuroPSI), CNRS & Paris-Saclay University, France. She is now a postdoctoral researcher in the lab of Prof. Marta Manser at the University of Zurich, Switzerland, investigating acoustic communication to decipher how vocal signals modulate social interactions in group-living mammals, in relation to the species' ecological constraints.

Low Computational Complexity RLS-Based Decision-Feedback Equalization in Underwater Acoustic Communications

Low Computational Complexity RLS-Based Decision-Feedback Equalization in Underwater Acoustic Communications