bluuebunny/crossref_metadata_2025 huggingface dataset:
Realtime integration of acoustic input and semantic expectations in speech processing: evidence from electroencephalography
Authors: Sarrett McCall E. , Kapnoula Efthymia , McMurray Bob
Published: October 2018

A critical question in speech perception is the relative independence of perceptual and semantic processing. Answering this requires addressing two issues. First, does perceptual processing complete before semantic processing (discrete stages vs. continuous cascades)? Second, do semantic expectations affect perceptual processing (feedback)? These questions are difficult to address as there are few measures of early perceptual processing for speech. We extend a recent electroencephalography (EEG) paradigm which has shown sensitivity to pre-categorical encoding of Voice-Onset Time (VOT; Toscano et al., 2010). By measuring the timecourse over which perceptual and semantic factors affect the neural signal, we quantify how these processes interact. Participants (N = 31) heard sentences (Good dogs also sometimes—) which biased them to expect a target word (bark rather than park). We manipulated VOT of the target word and coarticulation leading to it. A component-independent analysis determined when each cue affects the continuous EEG signal every 2 msec. This revealed an early window (125–225 msec) sensitive exclusively to bottom-up information, a late window (400–575 msec) sensitive to semantic information, and a critical intermediate window (225–350 msec) during which VOT and coarticulation are processed simultaneously with semantic expectations. This suggests continuous cascades and early interactions between perceptual and semantic processes.
Developing new pre-lexical processing skills in adults
Authors: Schmidt Anna M.
Published: October 2018

Studies of adults learning to decode words may provide a window on understanding of the pre-lexical processing of words as learning progresses. Second language (L2) learners (for example) have been found to assimilate new phones to first language (L1) phonemes when asked for the closest sound in their languages (e.g., Schmidt, 1996). Ratings of fit with L1 phonemes was related to details of acoustics of stimuli, L1 acoustics, and vowel context suggesting that L1 phonetic details rather than phoneme categories were compared. What happens after attention has been focused on acoustic/articulatory characteristics of these new sounds (as in training studies) and learning progresses? Do adults establish new phoneme categories to aid in word processing or is it more likely that native categories are expanded based upon developing within L1 category perceptual skills and orthographic word prediction skills. Evidence will be reviewed indicating that learned production of L2 sounds can be become native-like but L2 perception outcomes remain non-native like suggesting that new phoneme categories are not formed. Thus, new learned words can be accurately produced but success in pre-lexical processing of new heard words will depend upon linguistic factors such as context.
The acquisition of English stress by Kazakh-Russian bilinguals: The role of dominant language
Authors: Yakup Mahire
Published: October 2018

This study systematically investigates the cross-linguistic influence of the acquisition of English lexical stress by Kazakh-Russian bilinguals. Experiment 1 examined the Kazakh accent/stress pattern. Even though there is an argument about Kazakh stress, we used near minimal pairs in Kazakh such as balaDAR “children” vs. balaDAY “like a child, childish.” By measuring duration, intensity, and pitch on 20 Kazakh-Russian bilinguals with strong Kazakh language level, we compared the stressed syllable versus unstressed syllables in the near minimal pairs and found duration as a stronger cue for the stress/accent in the syllables. In experiment 2 we investigated the roles of Russian as the dominant language in cross-linguistic influences. We used ten minimal pairs in Russian produced by 20 Russian bilinguals who claimed their native language is Russian. The results showed Kazakh-Russian bilinguals produced Russian stress using duration. Experiment 3 focuses on the acquisition of stress pattern in English by Kazakh-Russian bilinguals. We recruited 40 participants with (IELTS= 7.0) producing 10 English minimal pairs in three conditions. We found that duration and intensity are stronger cues than F0. None of the group used F0 as a stress cue in English lexical stress. The result will be discussed regarding dominant Russian language.
Travel time tomography with local sparse modeling and dictionary learning
Authors: Bianco Michael J. , Gerstoft Peter
Published: October 2018

In this talk, we present a machine learning-based approach to 2D travel time tomography. Travel time tomography methods image slowness structures (e.g., Earth geology) from acoustic and seismic wave travel times across sensor arrays. Typically, slowness is obtained via an ill-posed linear inverse problem, which requires regularization to obtain physically plausible solutions. We propose to regularize this inversion by modeling rectangular groups of slowness pixels from the image, called patches, as sparse linear combinations of atoms from a dictionary. In this locally-sparse travel time tomography (LST) method, the dictionary, which represents elemental slowness features, is initially unknown and is learned from the travel time data using an unsupervised machine learning task called dictionary learning. This local model constrains small-scale slowness features, and is combined with a global model, which constrains larger-scale features with L2 regularization. In contrast to conventional regularization, which allows only for smoothness or discontinuous slowness, LST permits increased resolution where warranted by data. A maximum a posteriori formulation ofLST is derived, which is solved as an iterative algorithm. LST performance is evaluated on both synthetic and real data in the context of ambient noise tomography.
The use of context in machine learning for bioacoustics
Authors: Roch Marie A. , Baumann-Pickering Simone , Cholewiak Danielle , Fleishman Erica , Frasier Kaitlin E. , Glotin Herve , Helble Tyler A. , Hildebrand John , Klinck Holger , Lindeneau Scott , Liu Xiaobai , Nosal Eva-Marie , Palmer Kaitlin , Shiu Yu , Singh Gurisht
Published: October 2018

Biological acoustic signals are often produced in context. Contextual information includes things such as timing between calls, conspecific or interspecies cues, and physical environmental cues such as sunrise or sunset. We show how some forms of contextual information can be used to improve the results of detection and classification tasks for biological acoustic signals. We examine how context can be used to improve labeled data, resulting in more-accurate classification results, as well as how learners can exploit context directly. We demonstrate these improvements via two bioacoustic detection/classification tasks. The first algorithm detects odontocete echolocation clicks. We used a decision support system that allowed analysts to label echolocation clicks using between call timing cues as well as other measurements and found that deep learners trained with these high quality data are able to detect clicks in adverse environments. The second algorithm applies contextual information surrounding North Atlantic right whale upcalls to improve precision and recall. [This work was supported by ONR Grant Nos. N00014-17-1-2867 and N00014-15-1-2299.]
A sensitivity-based Bayesian hierarchical process for calibrating infrasound propagation models
Authors: Millet Christophe
Published: October 2018

Model calibration is viewed in the sense of adapting the full set of model parameters in order to get better resemblance between observations and major end-predictions. In this paper, we present a new probabilistic method to calibrate normal-mode-based propagation models using some observed data and sources of uncertainties. The unknown parameters are estimated using a multiple parallel Markov Chain Monte-Carlo method, for which convergence diagnostics are available. Using a few normal modes allows to rapidly estimate the statistical distributions of the arrival characteristics, on a mode-by-mode basis. In a sense, the unknown inputs "propagate" through the plausible waveguides with each mode and alters its amplitude and phase structure. The resulting waveform is obtained as a combination of individual wavepackets which depends continuously of the input parameters. Further, once the maximum likelihood has been identified, the reduced model can be extended to higher dimensions (with a larger number of modes) to better refine the calibration process. Numerical results are obtained using the FLOWS platform (Fast Low Order Wave Simulation), that integrate advanced spectral numerical methods and realistic representations of atmospheric disturbances. The method is used to revisit the infrasound signals recorded at I37NO during campaigns of ammunition destruction explosions at Hukkakero.
Graph clustering for localization within a sensor array
Authors: Gerstoft Peter
Published: October 2018

We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The method is applied to a dense 5200 element geophone array that blanketed 7 km ×10 km of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array.
Sparsity-based shipping noise analysis and cancellation in underwater acoustic communication
Authors: Zhang Ruoyu , Lampe Lutz , Zhao Honglin
Published: October 2018

We are interested in achieving reliable underwater acoustic communication (UWAC) in the presence of noise generated by vessel traffic, i.e., shipping noise. Our general approach is to determine an underlying structure in shipping noise and to exploit this structure to remove it from desired UWAC signals. Since a well-established statistical characterization of shipping noise is not available, in this paper, we discuss our evaluation of shipping noise data sets obtained from labeled recordings from an underwater acoustic hydrophone array deployed in the Strait of Georgia by Ocean Networks Canada. Motivated by the general observation that shipping noise exhibits a structure akin to impulse noise, we study to what extent shipping noise can be described as a sparse signal. Specifically, we apply the expectation-maximization method to train a Gaussian-mixture model with two components, in which the large variance component represents the impulse-noise part. In a second step, we use the model to perform noise cancellation in a multicarrier UWAC scenario. For this purpose, we apply a sparse-signal recovery formulation and a message passing algorithm for detection, i.e., a form of compressed sensing. Numerical results show the moderate level of mitigation of shipping noise interference achieved with the proposed method.
Compressive sound speed profile estimation with direction-of-arrivals
Authors: Choo Youngmin , Seong Woojae
Published: October 2018

Sound speed profile (SSP) predominates acoustic propagation in the ocean. In this work, the SSP is inverted using compressive sensing (CS) combined with direction of arrivals (DOAs) from beamforming. The travel times and the positions of the arrivals can be approximately linearized using their Taylor expansion with the shape function coefficients that parameterize the SSP. The linear relation between the travel times/positions and the shape function coefficients enables CS to reconstruct the SSP. The conventional objective function in CS is modified to simultaneously exploit the information from the travel times and positions. The proposed scheme is examined in the SWellEx-96 experimental environment.
Ship speed reduction is an effective mitigation for underwater noise effects
Authors: Wood Jason , Tollit Dominic , Joy Ruth
Published: October 2018

The Vancouver Fraser Port Authority’s ECHO Program led a voluntary 2-month ship slowdown trial during which 56% of piloted ships slowed down to <13 knots in a 16 nautical mile corridor. The goal was to determine if a slowdown could be used as a mitigation measure to reduce ship related underwater noise effects in core Southern Resident killer whale habitat. A calibrated hydrophone system was used to measure ambient noise levels from 10 Hz to 100 kHz during the trial and a representative 2-month baseline period. The hydrophone was located 2.3 (inbound) and 5 km (outbound) from the center of the shipping lanes at 23 m depth. Analyses of data with ships present showed a median broadband noise reduction of 2.5 dB. This reduction was highest in the 10–100 Hz decade band (3.1 dB) and lowest in the 10,000–100,000 Hz band (0.3 dB). A statistical model found that received noise levels were best described by the distance to ships, the presence of small boats, water velocity, slowdown period, ship speed through water, and wind speed. This highlights that appropriate temporal scales and the inclusion of covariate data are needed to adequately measure ship related changes in underwater ambient noise levels.
Multi-shipping sources classification method based on the line spectral components of shipping radiated noise
Authors: Jia Hongjian , Li Xiukun
Published: October 2018

The passive target detection based on shipping radiated noise is the key technology for underwater operations today. It has high research value both in civil and military applications. In this paper, the feature extraction of the underwater channels in the cepstrum domain is performed by using the line spectral components of the shipping radiated noise. The channel impulse response (CIR) function is used as the classification basis for the multi-shipping sources, and the line spectral components belonging to the same shipping source in the sonar received signal are searched to solve the classification problem of the multi-shipping radiated noise sources in the complex ocean background.
Stage-wise orthogonal matching pursuit for estimation of time delay and Doppler doubly spreading of underwater acoustic channels
Authors: Wu Feiyun , Yang Kunde , Sun Quan , Zhu Yunchao
Published: October 2018

The model of time delay and Doppler (DD) doubly spread is usually used for estimation of underwater acoustic channel (UAC) of time-varying and multi path. This study introduces the doubly spread model, then forms the optimization problem of channel estimations. By exploiting the sparsity of UAC, we propose the stage-wise orthogonal matching pursuit by inserting the orthogonal projection strategy on two domains. The traditional methods including least square (LS) based method, matching pursuit (MP), and orthogonal matching pursuit (OMP) methods are used for comparisons based on doubly spread models. Finally, the superiority of the proposed method is verified by experimental results.
Classification of multiple source depths in a time-varying ocean environment using a convolutional neural network (CNN)
Authors: Song Hee-Chun
Published: October 2018

Machine learning (ML) is the idea that there are generic algorithms that can tell us something interesting about a set of data without us having to write any custom code specific to the problem. Instead of writing code, we feed data to the generic algorithm and it builds its own logic based on the data. In this paper, ML is applied to classification of multiple (4) sources at various depths in a shallow-water waveguide where the input data are time-varying channel impulse responses (CIRs) received by a vertical array (4 hydrophones) from each of the sources over a period of 22 hours (528 examples). Specifically, the first 16 hours of CIRs are used for training a 4-layered CNN (convolutional neural net) to exploit the structure of CIRs in the two-dimensional time and depth domain, similar to image processing. Our hypothesis is that the dataset collected over a semi-diurnal tidal period (>12 hours) could capture the internal representations or feature vector needed for classification. The trained model is then tested on the next 6 hours of CIRs and achieves 98% accuracy, indicating the potential of ML in underwater applications.
Profiling musical audio processing effects with deep neural networks
Authors: Hawley Scott H. , Colburn Benjamin L. , Mimilakis Stylianos I.
Published: October 2018

Deep learning has demonstrated great performance in audio signal processing tasks such as source separation, dereverberation, and synthesis. A challenging effort in deep learning is to devise models that operate directly on the raw waveform signals (i.e., end-to-end). In this talk, we present attempts of an end-to-end task in audio signal processing, that we denote as profiling (i.e., emulation). Our objective is deep learning based profiling of a set of audio production and editing effects, including nonlinear time-dependent effects such as dynamic range compression and time alignment, as well as learning their parameterized controls (e.g., gain, attack time). We present some promising initial results. A consequence of using a data-driven approach to effects modeling is that it allows for the creation of novel audio effects purely via the construction and training on appropriate datasets, without explicitly devising a signal processing algorithm.
A low frequency underwater meta structure composed by helix metal and viscoelastic damping rubber
Authors: Zhang Ruihao
Published: October 2018

Many underwater acoustic absorption materials have been proposed, but good low frequency acoustic absorption remains a challenge. We report an underwater metastructure with excellent acoustic absorption that is constructed by perforating helixes of metal into viscoelastic damping rubber. Finite element analysis shows that this metastructure can achieve an acoustic absorption coefficient of 0.75 at about 100 Hz with a thickness of only 1/68 wavelength at the same frequency. Compared with a homogeneous viscoelastic rubber material, the addition of the helix structure improves the acoustic absorption ability in the range of 0–1,000 Hz. An analysis of vibration displacement maps indicates that waveform transformation, multiple scattering, and reflection energy dissipation mechanisms are the critical factors affecting the absorption performance. Different geometries and materials can adjust the sound absorption characteristics below 1,000 Hz. The proposed metastructure has the advantages of high acoustic absorption ability, broader frequency bandwidth, and regular geometry, providing more possibilities for underwater acoustic manipulation applications.
Computational medicine in voice research
Authors: Li-Jessen Nicole Y.
Published: October 2018

Computer models have been widely used to numerically simulate the physical dynamics of vocal fold oscillation in phonation. Computer simulations have allowed the exploration of a much wider parameter space and a much longer time scale than what would be very costly or sometimes impossible with animal and human models. In the past 10 years, our team uses a combined in vivo, in vitro, and in silico approach to understand the biological mechanism underlying the formation of vocal lesions. The ultimate goal is to identify key biological and physical factors associated with the pathogenesis of and recovery from vocal fold injury that will be useful for personalized voice restoration. Tissue injury and repair is a complex process that involves multiple cells types and molecular signals. We developed 3D agent-based models at a physiological scale to simulate and visualize the cellular and molecular response to vocal injury and treatment. Significant progress has made to improve the model’s computational speed and visualization features using our hybrid CPU-GPU computing platform. Gaps however still exist between the model and the reality. In this talk, I will present what we have achieved so far as well as what challenges we are facing in biological computing.
High-fidelity image-based computer modeling of voice production—From muscle contraction to flow-structure-acoustics interaction
Authors: Xue Qian , zheng Xudong , Jiang Weili , Pham Ngoc , Geng Biao
Published: October 2018

This study aims to develop a high-fidelity computer model of voice production which can employ the image-based realistic three-dimensional geometries of larynges and simulate the complex mechanical process of voice production and control, from muscle contraction to flow-structure-acoustics interactions. Such a model will advance our understanding of the relationship between muscle contraction, vocal fold posturing, vocal fold vibration, and final voice outcome, which has important clinical implications for voice management, training, and treatment. The key components of the model include a sharp-interface-immersed-boundary-method based impressible flow model, a finite-element method based nonlinear structural dynamics model and a hydrodynamics/acoustics splitting method based acoustics model. A Hill-based contractile model is coupled in the finite element analysis to capture the active response of vocal fold tissues, and a fiber-reinforced model is employed for the passive response. A series of validations have been performed. The coupled Hill-based model and fiber-reinforced model demonstrated a good agreement with literature experimental data for dynamics, concurrent tissue stimulation, and stretching. The flow-structure-acoustics interaction model was validated with excised canine experiments using realistic geometric and material properties. The simulations showed a good agreement on the fundamental frequency, vocal fold maximum divergent angle, flow rate, and intraglottal velocity and pressure fields.
The importance of medial surface vertical thickness to the control of voice production
Authors: Zhang Zhaoyan
Published: October 2018

While vocal fold vibration is often studied from a superior view, the vertical thickness of the vocal fold medial surface (or the portion that forms the glottal constriction) has long been hypothesized to play an important role in the control of voice production. This importance of the vertical thickness is confirmed in our recent computational studies, which showed that the vertical thickness, not the degree of vocal fold approximation, has a dominant effect on the vocal fold contact pattern and the spectral shape of the produced voice. Specifically, thicker folds often vibrate with a larger closed quotient, a lower H1-H2 value, and stronger excitation of higher-order harmonics. Thicker folds are also more likely to exhibit irregular vibration. These studies also showed an important effect of the transverse stiffness of the vocal fold in the coronal plane on the resulting voice quality, but a relatively small effect of the longitudinal tension on voice quality except around phonation onset. These results suggest that in addition to the superior view, more attention should be given to vocal fold shape along the vertical dimension and its control. [Work supported by NIH grant R01DC011299.]
Out-of-band beamforming in shallow water with horizontal arrays
Authors: Douglass Alexander S. , Abadi Shima , Dowling David R.
Published: October 2018

Out-of-band beamforming methods, frequency-difference and frequency-sum beamforming, are array signal processing methods that allow a user to process signals at either a lower, below-the-signal-band difference frequency, or higher, above-the-signal-band sum frequency. Frequency-difference beamforming has previously been investigated for shallow-ocean propagation with sparse vertical arrays, demonstrating its capability to overcome the negative effects of spatial aliasing [Douglass, Song, and Dowling (2017). J. Acoust. Soc. Am. 142, 1663–1673]. In the work presented here, data from the 2012 COAST (Cascadia Open-Access Seismic Transects) experiment is utilized to explore out-of-band methods with horizontal arrays, where variations in environmental characteristics (bathymetry, sound speeds, etc.) may be more pronounced across the array. The abundance of array elements (636 in total) and total array length (7.9 km) in this experiment provide a means for controlling the sparsity and signal coherence within a chosen subarray to determine the capabilities and limitations of out-of-band beamforming. In addition, the bandwidth of the signal of interest is sufficient to compare out-of-band methods to conventional methods where the difference or sum frequencies match the in-band frequency used with conventional beamforming. [Sponsored by ONR.]
Underwater acoustics array spatial reversal convolution and beamforming
Authors: Zhao Anbang , Ma Lin , Ge Chunsha , Bi Xuejie
Published: October 2018

A novel underwater acoustic array signal processing method based on spatial reversal and convolution, aiming at improving detection performance, is proposed to meet the engineering application demand of the underwater acoustic array detection system. The theoretical and mathematical model of the proposed method is deduced and presented in detail. Based on the extended covariance matrix of the physical array, the array sensitivity equalization and the noise suppression technique of the underwater acoustic array are studied. The additional gain provided by sensitivity equalization and noise suppression techniques is analyzed and exploited. Computer modelling and various numerical simulations are applied to demonstrate the proposed method’s effectiveness. At-sea experimental data are processed to test the performance in real underwater acoustic environment. These results indicate that the proposed array processing method can effectively improve the detection ability. The proposed techniques in this paper provide an insightful way to improve the detection performance of the underwater acoustic array.
Vibration isolation for world-class performance spaces, Part II: Examples
Authors: Phillips James E.
Published: October 2018

This paper will present examples of vibration isolation incorporated into world-class performance spaces in North America and oversees, including acoustical and vibration measurements demonstrating the effectiveness of the vibration isolation to reduce groundborne/structureborne noise.
Applying machine-learning based source separation techniques in the analysis of marine soundscapes
Authors: Lin Tzu-Hao , Akamatsu Tomonari , Tsao Yu , Fujikura Katsunori
Published: October 2018

Long-term monitoring of underwater soundscapes provides us a large number of acoustic recordings to study a marine ecosystem. Characteristics of a marine ecosystem, such as the habitat quality, composition of marine fauna, and the level of human interference, may be analyzed using information relevant to environmental sound, biological sound, and anthropogenic sound. Supervised source separation techniques have been widely employed in speech and music separation tasks, but it may not be practical for the analysis of marine soundscapes due to the lack of a database that includes a large mount of paired pure and mixed signals. Even when the paired data is not available, different sound sources with unique spectral or temporal patterns may still be separated by apply semi-supervised or unsupervised learning algorithms. In this presentation, supervised and unsupervised source separation techniques will be demonstrated on long-term spectrograms of a marine soundscape. Separation performances under different levels of simultaneous source influence will also be discussed. In the future, more advanced techniques of source separation are necessary to facilitate the soundscape-based marine ecosystem sensing. An open database of marine soundscape will promote the development of machine learning-based source separation. Therefore, we will open acoustic data tested in this presentation on the Asian Soundscape to encourage the open science of marine soundscape.
Identification of fish species in estuaries and rivers using recorded soundscape with supervised machine learning
Authors: Badiey Mohsen , Garcia-Frias Javier
Published: October 2018

Identification of various fish species in estuarine and riverine environments is an important ecological problem at the intersection of various disciplines, including underwater acoustics, signal processing, and fisheries. Advancements in this field can be made by applying machine learning and deep learning technologies. From the vast amount of existing work on machine learning techniques, of special relevance to this problem are those aiming at the detection and labeling of speakers on overlapping speech, where the existing literature is much more reduced. In this paper, we present a dataset collected with a passive recorder placed on a tripod in Delaware Bay estuary during summer 2013 to continuously measure environmental soundscapes for several weeks. By using a library of mid-Atlantic region fish sounds as prior knowledge, we adapt the aforementioned techniques to the detection and identification of various recorded sounds. This adaptation is challenging, as the statistical properties of fish sounds are not the same as those of speech, and requires careful research on how to perform data pre-processing, feature extraction, and model development. The application of the proposed machine learning techniques to future observations will enhance the potential for long-term autonomous ecological studies in bays and rivers.
Toward scalable, reproducible, and open ocean acoustic research
Authors: Staneva Valentina , Tan Amanda , Panicker Divya , Lee Wu-Jung
Published: October 2018

As our ability to collect long-term acoustical signals grows we face the challenges of analyzing large datasets, ensuring our findings are reproducible, and sharing our work with collaborators. In this talk, we will give an overview of frameworks and tools that can facilitate those tasks. We will show how the Jupyter Notebook environment serves as a hub for quick prototyping, literate programming, interactive analysis and visualization, and a gateway to cloud computing. We will provide examples of processing of larger-than-memory ocean acoustic recordings from the comfort of our own laptop. We will further outline best practices for sharing code and data, and discuss the needs and approaches to achieve scalable, reproducible, and open acoustic research.
Impact of stone characteristics on cavitation in burst wave lithotripsy
Authors: Hunter Christopher , Maxwell Adam D. , Cunitz Bryan , Dunmire Barbrina , Sorensen Matthew D. , Williams James C. , Bailey Michael , Randad Akshay , Kreider Wayne
Published: October 2018

Non-invasive kidney stone treatments such as shock wave lithotripsy (SWL) and burst wave lithotripsy (BWL) rely on the delivery of pressure waves through tissue to the stone. In both SWL and BWL, the potential to hinder comminution by exciting cavitation proximal to the stone has been reported. To elucidate how different stones alter prefocal cavitation in BWL, different natural and synthetic stones were treated in vitro using a therapy transducer operating at 350 kHz (peak negative pressure 7 MPa, pulse length 20 cycles, pulse repetition frequency 10 Hz). Stones were held in a confined volume of water designed to mimic the geometry of a kidney calyx, with the water filtered and degassed to maintain conditions for which the cavitation threshold (in the absence of a stone) matches that from in vivo observations. Stone targeting and cavitation monitoring were performed via ultrasound imaging using a diagnostic probe aligned coaxially with the therapy transducer. Quantitative differences in the extent and location of cavitation activity were observed for different stone types—e.g., “softer” stones (natural and synthetic) that disintegrate into dusty fragments produced larger prefocal cavitation clouds. Future work will focus on correlation of such cavitation metrics with stone fragmentation. [Funding support by NIH P01-DK043881, K01-DK104854.]
Ultrasonic and X-Ray tomography inspection of a woven glass reinforced composite damaged by fatigue loading
Authors: Miqoi Nada , Pomarède Pascal , Declercq Nico F. , Peltier Laurent , Meraghni Fodil
Published: October 2018

An investigation of a polyamide 6.6/6 composite reinforced with woven glass fibers is described with a focus on its response to fatigue solicitations. The main purpose is to elaborate a quantitative and a qualitative study of the induced damage as well as its detectability. To do so, several nondestructive testing methods were used. The different damage mechanisms, relative to fatigue loading, were identified using X-Ray tomography as a reference for the ultrasonic investigations. As a result, each damage mechanism is visualized and a measure of the induced void is established for comparison. An ultrasonic investigation based on C-scans and guided waves is performed under different signal analysis approaches in an attempt to extract as much information as possible. The discoveries and experiences are important in the framework of a collaboration with the automotive industry en for biomechanical applications.
The time course of recognition of reduced disyllabic Japanese words: Evidence from pupillometry with a Go-NoGo task
Authors: Mukai Yoichi , Tucker Benjamin V. , Järvikivi Juhani
Published: October 2018

While much attention has been paid to the importance of reduction in spoken word recognition, fewer studies have investigated the effect of reduction over time. Thirty-eight participants’ pupillary responses were measured during the perception of Japanese disyllabic words as they performed a Go-NoGo task. We used 226 lexical items, each of which contained both reduced and citation forms of the words. All stimuli consisted of a word-medial nasal or voiced stop. Results demonstrate that the overall amount of cognitive effort required to process reduced forms was higher than that of canonical forms. That is, greater pupil dilation was observed for reduced forms than for citation forms. This result is in line with previous research (e.g., Tucker, 2011). Specifically, pupil dilation was greater with reduced forms in the time window of 436 ms to 2000 ms after the onset of stimuli. Our results also indicate that the pattern of pupil dilation over time with reduced forms differs from citation forms, indicating that reduced forms show a later onset and offset of peak dilation and more gradual constriction of pupil compared to citation forms.
Passive detection parameter measurement of azimuth and frequency based on single vector sensor
Authors: Hui Juan , Song Mingyu , Li JiangQiao
Published: October 2018

This paper mainly studies the measurement technology of passive detection parameters based on single vector sensor. Ship radiated noise contains a lot of target information, so the extraction of the line noise of the ship's radiated noise is of great significance in the measurement of passive detection parameters. The radiation noise of the ship is a broadband spectrum modulated by the spectral signal envelope. In this paper, the mathematical model of the radiation noise of the ship is simulated and the demodulation of the ship's radiated noise is carried out by using the square demodulation and the absolute value demodulation. The average azimuth and complex intensifier are used to estimate and analyze the target azimuth, and the estimated angle is statistically processed by histogram and weighted histogram. For the frequency estimation technique, the adaptive frequency estimator based on the adaptive notch filter and the adaptive LMS (least mean square) algorithm is chosen to study the target signal frequency.Through the verification of the simulation experiment, the azimuth estimation technique and the adaptive frequency estimation technique are feasible. By estimating the azimuth sequence and frequency sequence of the target radiation signal, the relevant information of the target can be obtained, so it is of great significance in the research of underwater acoustic detection technology.
Prominence-marking mechanisms in emotional speech
Authors: Martins Marcus Vinicius Moreira , Ferreira-Netto Waldemar
Published: October 2018

The aim of this work is to investigate the prominence-marking mechanisms in emotional speech, particularly in Brazilian Portuguese intonational system. Three professional actresses interpreted a text in three conditions: anger, sadness and neutral, in a total of 130 sentences for each condition (n = 390). Others tests established the minimum value for a prominence mark is + 3 semitones from the mean fundamental frequency (F0). In the first analysis, it is observed the distribution of prominences frequencies (F0) is normal for neutral, but non-normal in the other two cases (skewness; anger = -1.45 and sadness = -0.5) and the difference between distributions is significant in all cases. In the rage and neutral conditions, the prominence is marked consistently 5 semitones above fundamental frequency mean, non-random, however in sadness the prominence-marking mechanism is almost random. A second frequency distribution test revealed the difference between distributions is significant between anger and other conditions (p <0.05), but it is not significant between sadness and neutral speech (p> 0.05). These data suggest that the distribution of frequencies in the pitch range combined with an analysis of the prominences may be a relevant criterion to distinguish the sadness from other emotions, especially in automatic recognition process.
Final devoicing in Singapore English
Authors: Chow Daryl , Kharlamov Viktor
Published: October 2018

This study investigates the voicing contrast in word-final obstruents in Singapore English. Previous auditory accounts have suggested that word-final obstruents undergo complete devoicing in Singapore English and become identical to their voiceless counterparts, including neutralization of differences in adjacent vowel duration (among others, Bao 1998, Wee 2008). On the basis of acoustic data from the NIESCEA corpus (Low 2015), we examine the extent to which voicing-related differences are neutralized when reading wordlists, sentences and passages as well as in unscripted conversations. Results suggest that neutralization is phonetically incomplete in Singapore English, with underlying voicing being recoverable from such parameters as closure voicing ratio and durations of consonants and adjacent vowels. These findings are in line with the results for other devoicing languages, such as German and Russian, that also show incomplete neutralization of the voicing contrast in final obstruents (e.g., Roettger et al. 2014, Kharlamov 2014).
The diphthongs of the acrolectal Kenyan English spoken by the Black Indigenous Kenyans
Authors: IRUMBI RUTH W. , Karia Mathew K. , Itumo Joshua M.
Published: October 2018

Kenya has three main varieties of English: the variety spoken by white Kenyans (WhKE), the acrolectal Kenyan English spoken by the Black Indigenous Kenyans (BIKE), and the mesolectal varieties, which are ethnically marked (Kioko & Muthwii, 2004; Hoffmann, 2010; Njoroge, 2011).There have been calls to describe the acrolectal variety of English .This paper documents the BIKE diphthongs based on data from a research carried out in 2016. The participants, seven males and seven females, were university lecturers who were purposively selected from the three major language groups in Kenya (Bantu, Cushitic and Nilotic). These respondents read “The Boy Who Cried Wolf”, a passage adapted for IPA English phonemic analyses. Four tokens for each of the eight RP diphthongs were sampled giving us 448 tokens. The recorded audio files were converted into .wav files for acoustic analysis using Praat (Version 6.0.05). The findings presented herein, show that KenE has six diphthongs: / ai/, /oi/, /ua/, /ia/, /ea/, /ua/ and /au/, which are acoustically different from the eight RP diphthongs. In this paper, we explain how the BIKE diphthongs differ from the RP ones; describe how they cluster based on the gliding; and also map them in the vowel trapezium.
Reduced coarticulation and aging
Authors: Fougeron Cécile , D'Alessandro Daria , Lancia Leonardo
Published: October 2018

Lifespan changes in speech have mostly been documented with respects to children’s development, while little is known about its evolution throughout adulthood. More particularly our knowledge on the effect of aging on speech and voice is sparse. Changes have been found in voice quality [e.g., Xue & Hao, 2003], the speech rate has been described to slow down [e.g., Staiger et al. 2017), and pitch is said to raise for older males and to lower for older females [e.g., Harnsberger et al., 2008]. The present study aims to investigate the effect of aging on Vowelto_Vowel anticipatory coarticulation in French. This effect is tested according to vowel duration and to differences in regional varieties. Data from 240 speakers (half female) distributed across three age groups (20–45), (50–69), and (70–80) have been extracted from the MonPaGeHA database [Fougeron et al. 2018] which includes speakers from four regional varieties: France, Belgium, Switzerland, and Quebec. The influence of V2 (/a/ or /i/) on V1 (/a/) is measured as a lowering of F1 and a rise of F2. Results show that coarticulation and vowel duration varies with regional variety and that vowels of older speakers are lengthened. More interestingly, results show a reduction of coarticulation with age.
SOUND STREAM: Towards vocal sound synthesis via dual-handed simultaneous control of articulatory parameters
Authors: Saha Pramit , Mohapatra Debasish R. , Srungarapu Venkata Praneeth , Fels Sid
Published: October 2018

This paper introduces Sound stream: a low-cost, tangible and ambidextrous controller which drives a dynamic muscle-based model of the human vocal tract for articulatory speech synthesis. The controller facilitates the multidimensional inputs which are mapped to the tongue muscles in a biomechanical modeling toolkit Artisynth using a microcontroller. As the vocal tract is a complex biological structure containing many muscles, it is a challenging and computationally expensive task to accommodate control for every muscle in the proposed scheme. So, we have followed a simplified approach by controlling the selective muscles for the efficient articulatory speech synthesis. The goal for designing an ambidextrous controller is to create new possibilities of controlling multiple parameters to vary the tongue position and shape simultaneously for generating various expressive vocal sounds. As a demonstration, the user learns to interact and control a mid-sagittal view of the tongue structure in Artisynth through a set of sensors using both hands. The Sound-Stream explores and evaluates the appropriate input and mapping methods to design a controllable speech synthesis engine. 1. Wang, J. et al. (2011) “Squeezy: Extending a multi-touch screen with force sensing objects for controlling articulatory synthesis,” in Proceedings on New Interfaces for Musical Expression, Oslo, Norway, pp. 531–532.
Toward the automatic detection of manually labeled irregular pitch periods
Authors: Murton Olivia , Rosas-Smith Sophie , Choi Jeung-Yoon , Mehta Daryush , Shattuck-Hufnagel Stefanie
Published: October 2018

Irregular pitch periods (IPPs) occur in a wide variety of speech contexts and can support automatic speech recognition (ASR) systems by signaling word boundaries, phrase endings, and certain prosodic contours. IPPs can also provide information about emotional content, dialect, and speaker identity. The ability to automatically detect IPPs is particularly useful because accurately identifying IPPs by hand is time-consuming and requires expertise. In this project, we use an algorithm developed for creaky voice analysis by Kane et al. (2013) incorporating features from Ishi et al. (2008) to automatically identify IPPs in recordings of speech from the American English Map Task (AEMT) database. Short-term power, intra-frame periodicity, inter-pulse similarity, subharmonic energy, and glottal pulse peakiness measures are input into an artificial neural network to generate frame-by-frame creak probabilities. To determine a perceptually relevant threshold probability, the creak probabilities are compared to IPPs hand-labeled by experienced raters. Preliminary results from four AEMT conversations yielded an area under the receiver operating characteristic curve of 0.898 on average. A creak probability threshold of 0.0083 yielded equivalent sensitivity and specificity of 81.1%. This study indicates generally good automatic detection of hand-labeled IPPs and explores the effects of linguistic and prosodic context.
Maximum likelihood geoacoustic inversion from surface generated noise
Authors: Gebbie John , Siderius Martin
Published: October 2018

Noise generated at the surface from wind and breaking waves is incident upon the seabed at a wide range of angles and frequencies. The reflectivity of the seabed thus plays an important role in determining the vertical directionality of the noise field. It is therefore not surprising that from an information theory perspective, the noise field encodes a significant amount of information about the geoacoustic properties of the seabed that govern reflectivity, such as layering structure, sound speed, density, and attenuation. Using a physics-based ambient noise model, the Cramér-Rao lower bound (CRLB) can be computed, which specifies the lowest possible variance that an unbiased estimator can have. Existing estimators have primarily involved vertically beamforming the noise field to recover the vertical noise directionality and bottom loss, which is then processed to estimate geoacoustic seabed properties. The method described here takes a different approach by estimating the properties directly from the measured data (i.e., without beamforming). This presentation will show that maximizing the proposed likelihood function can perform better than beamforming-based techniques, and approaches the CRLB. Further, it remains unbiased in low signal-to-noise ratio conditions, is tolerant to array tilt, and can operate beyond the nominal array design frequency.
Classifying seabed parameters from normal incidence reflections
Authors: Frantz Megan , Siderius Martin , Schecklman Scott
Published: October 2018

A technique is being investigated to estimate and classify seabed parameters, including interface roughness, based on normal incident reflections. These parameters can be characterized by single beam echo sounder data or normal beams from a side scan sonar. Previous sediment classification methods used either empirical relationships based on grain size (estimated based on the strength of the echo return) or by matching data with a parameterized model of the echo envelope. [Snellen, Siemes, Simons. J Acoust Soc Am. 2011]. Here, seabed classification (including interface roughness) is estimated using a combined approach. Both the strength of the reflection and a model of the echo envelope are used to determine seabed properties. The modelled envelope is obtained from the parameterization of the scattering cross section derived from the high-frequency Kirchhoff approximation near vertical incidence [ Jackson, Richardson. High-Frequency Seafloor Acoustics]. To determine the validity of the modelling approximations, a merit function has been developed to quantify the similarity between the data returned and the model results. In this presentation, the model-based approach to classifying seabed properties will be described along with results showing the exact and approximate scattering results. [Work supported by the Office of Naval Research.]