Speech perception as information processing.

The Reflections series takes a look back on historical articles from The Journal of the Acoustical Society of America that have had a significant impact on the science and practice of acoustics.

Vocal repertoire of Microhyla nilphamariensis from Delhi and comparison with closely related M. ornata populations from the western coast of India and Sri Lanka.

Advertisement calls in frogs have evolved to be species-specific signals of recognition and are therefore considered an essential component of integrative taxonomic approaches to identify species and delineate their distribution range. The species rich genus Microhyla is a particularly challenging group for species identification, discovery and conservation management due to the small size, conserved morphology and wide distribution of its members, necessitating the need for a thorough description of their vocalization. In this study, we provide quantitative description of the vocal behaviour of Microhyla nilphamariensis, a widely distributed south Asian species, from Delhi, India, based on call recordings of 18 individuals and assessment of 21 call properties. Based on the properties measured acrossed 360 calls, we find that a typical advertisement call of M. nilphamariensis lasts for 393.5 ±  57.5 ms, has 17 pulses on average and produce pulses at rate of 39 pulses/s. The overall call dominant frequency was found to be 2.8 KHz and the call spectrum consisted of two dominant frequency peaks centered at 1.6 KHz and 3.6 KHz, ranging between 1.5-4.1 KHz. Apart from its typical advertisement call, our study also reveals the presence of three 'rare' call types, previously unreported in this species. We describe variability in call properties and discuss their relation to body size and temperature. We found that overall dominant frequency 1 (spectral property) was found to be correlated with body size, while first pulse period (temporal property) was found to be correlated with temperature. Further, we compare the vocal repertoire of M. nilphamariensis with that of the congener Microhyla ornata from the western coast of India and Sri Lanka and also compare the call properties of these two populations of M. ornata to investigate intra-specific call variation. We find statistically significant differentiation in their acoustic repertoire in both cases. Based on 18 call properties (out of 20), individuals of each locality clearly segregate on PCA factor plane forming separate groups. Discriminant function analysis (DFA) using PCA factors shows 100% classification success with individuals of each locality getting classified to a discrete group. This confirms significant acoustic differentiation between these species as well as between geographically distant conspecifics. The data generated in this study will be useful for comparative bioacoustic analysis of Microhyla species and can be utilized to monitor populations and devise conservation management plan for threatened species in this group.

Introduction to the special issue on fish bioacoustics: Hearing and sound communicationa).

Fish bioacoustics, or the study of fish hearing, sound production, and acoustic communication, was discussed as early as Aristotle. However, questions about how fishes hear were not really addressed until the early 20th century. Work on fish bioacoustics grew after World War II and considerably in the 21st century since investigators, regulators, and others realized that anthropogenic (human-generated sounds), which had primarily been of interest to workers on marine mammals, was likely to have a major impact on fishes (as well as on aquatic invertebrates). Moreover, passive acoustic monitoring of fishes, recording fish sounds in the field, has blossomed as a noninvasive technique for sampling abundance, distribution, and reproduction of various sonic fishes. The field is vital since fishes and aquatic invertebrates make up a major portion of the protein eaten by a signification portion of humans. To help better understand fish bioacoustics and engage it with issues of anthropogenic sound, this special issue of The Journal of the Acoustical Society of America (JASA) brings together papers that explore the breadth of the topic, from a historical perspective to the latest findings on the impact of anthropogenic sounds on fishes.

Accurate species classification of Arctic toothed whale echolocation clicks using one-third octave ratios.

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.

Characteristics of wild moose (Alces alces) vocalizations.

Moose are a popular species with recreationists but understudied acoustically. We used publicly available videos to characterize and quantify the vocalizations of moose in New Hampshire separated by age/sex class. We found significant differences in peak frequency, center frequency, bandwidth, and duration across the groups. Our results provide quantification of wild moose vocalizations across age/sex classes, which is a key step for passive acoustic detection of this species and highlights public videos as a potential resource for bioacoustics research of hard-to-capture and understudied species.

Effect of Akson Therapy on Acoustic Parameters in Patients with Functional Dysphonia.

OBJECTIVE: Functional dysphonia can impair the language expression ability and adversely affect the career development of some patients. Therefore, an active exploration of effective treatment options is imperative. This study investigated the effect of Akson therapy on acoustic parameters in patients with functional dysphonia. MATERIALS AND METHODS: In this retrospective analysis, 79 patients with functional dysphonia who received conventional voice correction training from June 2020 to June 2021 were included in the reference group (RG). Our hospital has implemented Akson therapy since July 2021. Correspondingly, 72 patients with functional dysphonia who underwent Akson therapy from July 2021 to July 2022 were enrolled in the observation group (OG). The acoustic parameters such as fundamental frequency (F0), jitter, shimmer, and normalized noise energy (NNE); the aerodynamic parameters including maximum phonation time (MPT), mean airflow rate (MFR), and Voice Handicap Index-10 (VHI-10) score; and the Grade, Roughness, Breathiness, Asthenia, and Strain scale (GRBAS) score were measured before and after treatment and compared between the two groups. RESULTS: The F0, jitter, shimmer, NNE, MPT, and MFR values as well as the VHI-10 score and the grade (G), roughness (R), and breathiness (B) scores on the GRBAS did not significantly differ between the two groups before treatment (P > 0.05). However, significantly lower F0, jitter, shimmer, NNE, and MFR values and higher MPT levels were found in the OG compared to the RG after treatment (P < 0.001). Furthermore, the VHI-10 score and the G, R, and B scores were significantly lower in the OG than in the RG after treatment (P < 0.001), whereas the asthenia (A) and strain (S) scores remained at 0 before and after treatment. CONCLUSION: Akson therapy can improve the acoustic parameters of patients with functional dysphonia to a certain extent, indicating its potential application value.

Effects of duty cycle on passive acoustic monitoring metrics: The case of blue whale songs.

Long-term fixed passive acoustic monitoring of cetacean populations is a logistical and technological challenge, often limited by the battery capacity of the autonomous recorders. Depending on the research scope and target species, temporal subsampling of the data may become necessary to extend the deployment period. This study explores the effects of different duty cycles on metrics that describe patterns of seasonal presence, call type richness richness, and daily call rate of three blue whale acoustics populations in the Southern Indian Ocean. Detections of blue whale calls from continuous acoustic data were subsampled with three different duty cycles of 50%, 33%, and 25% within listening periods ranging from 1 min to 6 h. Results show that reducing the percentage of recording time reduces the accuracy of the observed seasonal patterns as well as the estimation of daily call rate and call call type richness. For a specific duty cycle, short listening periods (5-30 min) are preferred to longer listening periods (1-6 h). The effects of subsampling are greater the lower the species' vocal activity or the shorter their periods of presence. These results emphasize the importance of selecting a subsampling scheme adapted to the target species.

Analysis of factors on voice quality in thyroidectomy patients.

OBJECTIVE: Vocal cord paralysis (VCP) is a serious complication in thyroidectomy operations; however, its management remains unclear. The present study evaluated the voice parameters of patients who underwent surgery using Intraoperative Neurophysiologic Monitoring (IONM). PATIENTS AND METHODS: A total of 52 patients (41 females and 11 males) who underwent a total thyroidectomy operation were evaluated using objective and subjective voice analysis examinations before and after surgery. Acoustic parameters, such as Fundamental Frequency (F0), Shimmer, Jitter, Noise-to-Harmonic ratio (NHR), and aerodynamic parameters, including S/Z ratio and maximum phonation time (MPT), were analyzed. Objective findings, including the VHI-10 (Voice Handicap Index) and V-RQOL (Voice-Related Quality of Life), were also analyzed. The relationship between voice parameters and IONM values was investigated. RESULTS: The objective analysis (acoustic and aerodynamic parameters) showed no difference (p>0.05). However, the subjective analysis, which involved the VHI-10 and V-RQOL measures, revealed a significant difference before and after the operation (p<0.05). The Spearman correlation analysis showed that the NHR postoperative 1st-month parameter negatively correlated (rho=-0.317, p<0.059), while the F0 postoperative 6th-month parameter positively correlated (rho=0.347) with the amplitude difference before and after dissection (Right R2-R1 difference) for the right RLN measured in IONM. CONCLUSIONS: Patients who are planning to undergo a thyroidectomy procedure should undergo voice assessment during both the preoperative and postoperative periods. IONM could improve voice quality outcomes.

Perceptual formant discrimination during speech movement planning.

Evoked potential studies have shown that speech planning modulates auditory cortical responses. The phenomenon's functional relevance is unknown. We tested whether, during this time window of cortical auditory modulation, there is an effect on speakers' perceptual sensitivity for vowel formant discrimination. Participants made same/different judgments for pairs of stimuli consisting of a pre-recorded, self-produced vowel and a formant-shifted version of the same production. Stimuli were presented prior to a "go" signal for speaking, prior to passive listening, and during silent reading. The formant discrimination stimulus /uh/ was tested with a congruent productions list (words with /uh/) and an incongruent productions list (words without /uh/). Logistic curves were fitted to participants' responses, and the just-noticeable difference (JND) served as a measure of discrimination sensitivity. We found a statistically significant effect of condition (worst discrimination before speaking) without congruency effect. Post-hoc pairwise comparisons revealed that JND was significantly greater before speaking than during silent reading. Thus, formant discrimination sensitivity was reduced during speech planning regardless of the congruence between discrimination stimulus and predicted acoustic consequences of the planned speech movements. This finding may inform ongoing efforts to determine the functional relevance of the previously reported modulation of auditory processing during speech planning.

Aquatic Soundscape Recordings Reveal Diverse Vocalizations and Nocturnal Activity of an Endangered Frog.

AbstractAutonomous sensors provide opportunities to observe organisms across spatial and temporal scales that humans cannot directly observe. By processing large data streams from autonomous sensors with deep learning methods, researchers can make novel and important natural history discoveries. In this study, we combine automated acoustic monitoring with deep learning models to observe breeding-associated activity in the endangered Sierra Nevada yellow-legged frog (Rana sierrae), a behavior that current surveys do not measure. By deploying inexpensive hydrophones and developing a deep learning model to recognize breeding-associated vocalizations, we discover three undocumented R. sierrae vocalization types and find an unexpected temporal pattern of nocturnal breeding-associated vocal activity. This study exemplifies how the combination of autonomous sensor data and deep learning can shed new light on species' natural history, especially during times or in locations where human observation is limited or impossible.

Sex differences in vocal behavior in virtual rooms compared to real rooms.

This study investigates speech production under various room acoustic conditions in virtual environments, by comparing vocal behavior and the subjective experience of speaking in four real rooms and their audio-visual virtual replicas. Sex differences were explored. Males and females (N = 13) adjusted their voice levels similarly to room acoustic changes in the real rooms, but only males did so in the virtual rooms. Females, however, rated the visual virtual environment as more realistic compared to males. This suggests a discrepancy between sexes regarding the experience of realism in a virtual environment and changes in objective behavioral measures such as voice level.

Efficient Speech Detection in Environmental Audio Using Acoustic Recognition and Knowledge Distillation.

The ongoing biodiversity crisis, driven by factors such as land-use change and global warming, emphasizes the need for effective ecological monitoring methods. Acoustic monitoring of biodiversity has emerged as an important monitoring tool. Detecting human voices in soundscape monitoring projects is useful both for analyzing human disturbance and for privacy filtering. Despite significant strides in deep learning in recent years, the deployment of large neural networks on compact devices poses challenges due to memory and latency constraints. Our approach focuses on leveraging knowledge distillation techniques to design efficient, lightweight student models for speech detection in bioacoustics. In particular, we employed the MobileNetV3-Small-Pi model to create compact yet effective student architectures to compare against the larger EcoVAD teacher model, a well-regarded voice detection architecture in eco-acoustic monitoring. The comparative analysis included examining various configurations of the MobileNetV3-Small-Pi-derived student models to identify optimal performance. Additionally, a thorough evaluation of different distillation techniques was conducted to ascertain the most effective method for model selection. Our findings revealed that the distilled models exhibited comparable performance to the EcoVAD teacher model, indicating a promising approach to overcoming computational barriers for real-time ecological monitoring.

Mechanistic Assessment of Cardiovascular State Informed by Vibroacoustic Sensors.

Monitoring blood pressure, a parameter closely related to cardiovascular activity, can help predict imminent cardiovascular events. In this paper, a novel method is proposed to customize an existing mechanistic model of the cardiovascular system through feature extraction from cardiopulmonary acoustic signals to estimate blood pressure using artificial intelligence. As various factors, such as drug consumption, can alter the biomechanical properties of the cardiovascular system, the proposed method seeks to personalize the mechanistic model using information extracted from vibroacoustic sensors. Simulation results for the proposed approach are evaluated by calculating the error in blood pressure estimates compared to ground truth arterial line measurements, with the results showing promise for this method.

Label-free separation of peripheral blood mononuclear cells from whole blood by gradient acoustic focusing.

Efficient techniques for separating target cells from undiluted blood are necessary for various diagnostic and research applications. This paper presents acoustic focusing in dense media containing iodixanol to purify peripheral blood mononuclear cells (PBMCs) from whole blood in a label-free and flow-through format. If the blood is laminated or mixed with iodixanol solutions while passing through the resonant microchannel, all the components (fluids and cells) rearrange according to their acoustic impedances. Red blood cells (RBCs) have higher effective acoustic impedance than PBMCs. Therefore, they relocate to the pressure node despite the dense medium, while PBMCs stay near the channel walls due to their negative contrast factor relative to their surrounding medium. By modifying the medium and thus tuning the contrast factor of the cells, we enriched PBMCs relative to RBCs by a factor of 3600 to 11,000 and with a separation efficiency of 85%. That level of RBC depletion is higher than most other microfluidic methods and similar to that of density gradient centrifugation. The current acoustophoretic chip runs up to 20 µl/min undiluted whole blood and can be integrated with downstream analysis.

Articulatory and acoustic differences between lyric and dramatic singing in Western classical music.

Within the realm of voice classification, singers could be sub-categorized by the weight of their repertoire, the so-called "singer's Fach." However, the opposite pole terms "lyric" and "dramatic" singing are not yet well defined by their acoustic and articulatory characteristics. Nine professional singers of different singers' Fach were asked to sing a diatonic scale on the vowel /a/, first in what the singers considered as lyric and second in what they considered as dramatic. Image recording was performed using real time magnetic resonance imaging (MRI) with 25 frames/s, and the audio signal was recorded via an optical microphone system. Analysis was performed with regard to sound pressure level (SPL), vibrato amplitude, and frequency and resonance frequencies as well as articulatory settings of the vocal tract. The analysis revealed three primary differences between dramatic and lyric singing: Dramatic singing was associated with greater SPL and greater vibrato amplitude and frequency as well as lower resonance frequencies. The higher SPL is an indication of voice source changes, and the lower resonance frequencies are probably caused by the lower larynx position. However, all these strategies showed a considerable individual variability. The singers' Fach might contribute to perceptual differences even for the same singer with regard to the respective repertoire.

Conducting high-quality and reliable acoustic analysis: A tutorial focused on training research assistants.

Open science practices have led to an increase in available speech datasets for researchers interested in acoustic analysis. Accurate evaluation of these databases frequently requires manual or semi-automated analysis. The time-intensive nature of these analyses makes them ideally suited for research assistants in laboratories focused on speech and voice production. However, the completion of high-quality, consistent, and reliable analyses requires clear rules and guidelines for all research assistants to follow. This tutorial will provide information on training and mentoring research assistants to complete these analyses, covering areas including RA training, ongoing data analysis monitoring, and documentation needed for reliable and re-creatable findings.

Lesions in a songbird vocal circuit increase variability in song syntax.

Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC's recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by 'breaks' in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.

Facial Expression Recognition for Measuring Jurors' Attention in Acoustic Jury Tests.

The perception of sound greatly impacts users' emotional states, expectations, affective relationships with products, and purchase decisions. Consequently, assessing the perceived quality of sounds through jury testing is crucial in product design. However, the subjective nature of jurors' responses may limit the accuracy and reliability of jury test outcomes. This research explores the utility of facial expression analysis in jury testing to enhance response reliability and mitigate subjectivity. Some quantitative indicators allow the research hypothesis to be validated, such as the correlation between jurors' emotional responses and valence values, the accuracy of jury tests, and the disparities between jurors' questionnaire responses and the emotions measured by FER (facial expression recognition). Specifically, analysis of attention levels during different statuses reveals a discernible decrease in attention levels, with 70 percent of jurors exhibiting reduced attention levels in the 'distracted' state and 62 percent in the 'heavy-eyed' state. On the other hand, regression analysis shows that the correlation between jurors' valence and their choices in the jury test increases when considering the data where the jurors are attentive. The correlation highlights the potential of facial expression analysis as a reliable tool for assessing juror engagement. The findings suggest that integrating facial expression recognition can enhance the accuracy of jury testing in product design by providing a more dependable assessment of user responses and deeper insights into participants' reactions to auditory stimuli.

Correlation between acoustic characteristics and sensory evaluation of puffed-grain food based on energy analysis.

Puffed-grain food is a crispy snack whose consumer satisfaction depends on snack crispness and crunchiness, which can be characterized by the sound and the acoustic signals of food breaking. This study aimed to evaluate whether acoustic characteristics can be used to predict the crispness of various puffed-grain food. Sensory evaluation was performed on puffed-grain products with varying hygroscopic durations and different types. The relation between sensory evaluation and acoustic characteristics of nine different types of food was examined. The Hilbert-Huang transform was used to perform energy segmentation of the acoustic signal of puffed-grain food and observe its energy migration process. The results showed that energy release was more concentrated in the low-frequency range for grain-puffed foods with different hygroscopic durations. No notable correlation was observed between the low-frequency interval and sensory crispness for the different types of puffed-grain foods. However, the acoustic features extracted from their inherent low-frequency intervals showed a significantly improved correlation with sensory crispness. Therefore, it provides a theoretical reference for applying acoustic characteristics to describe food texture.

Domain-adaptation method between acoustic-response data using different insert earphones.

Classifying acoustic responses captured through earphones offers valuable insights into nearby environments, such as whether the earphones are in or out of the ear. However, the performances of classification algorithms often suffer when applied to other devices due to domain mismatches. This study proposes a domain-adaptation method tailored for acoustic-response data from two distinct insert earphone models. The method trains a domain-adaptation function using a pair of datasets obtained from a set of acoustic loads, yielding a domain-adapted dataset suitable for training classification algorithms in a target domain. The effectiveness of this approach is validated through assessments of domain adaptation quality and resulting performance enhancements in the classification algorithm tasked with discerning whether an earphone is positioned inside or outside the ear. Importantly, our method requires significantly fewer measurements than the original dataset, reducing data collection time while providing a suitable training dataset for the target domain. Additionally, the method's reusability across future devices streamlines data collection time and efforts for the future devices.