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A numerical simulation of sibilant /s/ production with the realistically moving vocal tract was conducted to investigate the flow and acoustic characteristics during the articulation process of velopharyngeal closure and tongue movement. The articulation process was simulated from the end of /u/ to the middle of /s/ in the Japanese word /usui/, including the tongue elevation and the velopharyngeal valve closure. The time-dependent vocal tract geometry was reconstructed from the computed tomography scan. The moving immersed boundary method with the hierarchical structure grid was adopted to approach the complex geometry of the human speech organs. The acoustic characteristics during the co-articulation process were observed and consistent with the acoustic measurement for the subject of the scan. The further simulations with the different closing speeds of the velopharyngeal closure showed that the far-field sound during the co-articulation process was amplified with the slower closing case, and the velum closure speed was inverse proportional to the sound amplitude with the slope value of − 35.3 dB s/m. This indicates possible phonation of indistinguishable aeroacoustics sound between /u/ and /s/ with slower velopharyngeal closure. [ABSTRACT FROM AUTHOR]

Many birds emit tonal song syllables even though the sound sources generate sound with rich upper harmonic energy content. This tonality is thought to arise in part from dynamically adjusted filtering of harmonic content. Here, we compare tonality of song syllables between vocal learners and non-learners to assess whether this characteristic is linked to the increased neural substrate that evolved with vocal learning. We hypothesize that vocal learning ability is correlated with enhanced ability for generating tonal sounds, because vocal production learners might also have an enhanced ability to articulate their vocal tracts and sound source for producing tonality. To test this hypothesis, we compared vocal learners and non-learners from two groups (186 passerines and 42 hummingbirds) by assessing tonality of song syllables. The data suggest that vocal learners in both clades have evolved to sing songs with higher tonality than the related, non-vocal learning clades, which is consistent with stronger roles for broadband dynamic filtering and adjustments to the sound source. In addition, oscine songs display higher tonality than those of hummingbirds. A complex interplay of vocal tract biomechanics, anatomical differences of the sound source as well as increased motor control through vocal learning facilitates generation of broad tonality. [ABSTRACT FROM AUTHOR]

Perception of speech sounds has a long history of being compared to perception of nonspeech sounds, with rich and enduring debates regarding how closely they share similar underlying processes. In many instances, perception of nonspeech sounds is directly compared to that of speech sounds without a clear explanation of how related these sounds are to the speech they are selected to mirror (or not mirror). While the extreme acoustic variability of speech sounds is well documented, this variability is bounded by the common source of a human vocal tract. Nonspeech sounds do not share a common source, and as such, exhibit even greater acoustic variability than that observed for speech. This increased variability raises important questions about how well perception of a given nonspeech sound might resemble or model perception of speech sounds. Here, we offer a brief review of extremely diverse nonspeech stimuli that have been used in the efforts to better understand perception of speech sounds. The review is organized according to increasing spectrotemporal complexity: random noise, pure tones, multitone complexes, environmental sounds, music, speech excerpts that are not recognized as speech, and sinewave speech. Considerations are offered for stimulus selection in nonspeech perception experiments moving forward. [ABSTRACT FROM AUTHOR]

In this work, we address the problem of creating a 3D dynamic atlas of the vocal tract that captures the dynamics of the articulators in all three dimensions in order to create a global speaker model independent of speaker-specific characteristics. The core steps of the proposed method are the temporal alignment of the real-time MR images acquired in several sagittal planes and their combination with adaptive kernel regression. As a preprocessing step, a reference space was created to be used in order to remove anatomical information of the speakers and keep only the variability in speech production for the construction of the atlas. The adaptive kernel regression makes the choice of atlas time points independently of the time points of the frames that are used as an input for the construction. The evaluation of this atlas construction method was made by mapping two new speakers to the atlas and by checking how similar the resulting mapped images are. The use of the atlas helps in reducing subject variability. The results show that the use of the proposed atlas can capture the dynamic behavior of the articulators and is able to generalize the speech production process by creating a universal-speaker reference space. [ABSTRACT FROM AUTHOR]

This paper investigates the production of Arabic gutturals by native (NSs) and non-native speakers (NNSs) of Arabic. A total of 40 participants, 20 NSs and 20 NNSs were recruited. 240 tokens were collected using two major methods: free speech and nonsense word testing. Using PRAAT software (version 6.1.01), the tokens were analyzed acoustically to measure F1 and F2 and to signal the (non)significance of the difference between the target groups and auditorily to rate gutturals' production accuracy by NNSs. F1 and F2 of the vowels neighbouring the gutturals were normalized using the speaker extrinsic Labov ANAE method (NORM version 1.1) to eliminate the effects of gender and age. The study demonstrates some important findings: in terms of quality, the F1-F2 approximation varies by nativeness in that NNSs were unable to make enough coarticulatory effects associated with Arabic gutturals. This result indicates that NNSs do not make a sufficient primary constriction in the posterior regions of the vocal tract. Relying on auditory judgments of accuracy, the most accurately produced gutturals by NNSs were the voiceless glottal fricative /h/ followed by the voiceless glottal plosive /ʔ/, and the lowest ranked gutturals were the voiced velar fricative /ɣ/ and the voiced pharyngeal fricative /ʕ/. The study concludes that non-temporal cues especially F1 and F2 are essential correlates to Arabic gutturals' production. Because such factors are language-specific, they should be taken into consideration in the teaching of Arabic as a second/foreign language. [ABSTRACT FROM AUTHOR]

Language resources are the main factor in speech-emotion-recognition (SER)-based deep learning models. Thai is a low-resource language that has a smaller data size than high-resource languages such as German. This paper describes the framework of using a pretrained-model-based front-end and back-end network to adapt feature spaces from the speech recognition domain to the speech emotion classification domain. It consists of two parts: a speech recognition front-end network and a speech emotion recognition back-end network. For speech recognition, Wav2Vec2 is the state-of-the-art for high-resource languages, while XLSR is used for low-resource languages. Wav2Vec2 and XLSR have proposed generalized end-to-end learning for speech understanding based on the speech recognition domain as feature space representations from feature encoding. This is one reason why our front-end network was selected as Wav2Vec2 and XLSR for the pretrained model. The pre-trained Wav2Vec2 and XLSR are used for front-end networks and fine-tuned for specific languages using the Common Voice 7.0 dataset. Then, feature vectors of the front-end network are input for back-end networks; this includes convolution time reduction (CTR) and linear mean encoding transformation (LMET). Experiments using two different datasets show that our proposed framework can outperform the baselines in terms of unweighted and weighted accuracies. [ABSTRACT FROM AUTHOR]

Purpose: Numerous MRI applications require data from external devices. Such devices are often independent of the MRI system, so synchronizing these data with the MRI data is often tedious and limited to offline use. In this work, a hardware and software system is proposed for acquiring data from external devices during MR imaging, for use online (in real‐time) or offline. Methods: The hardware includes a set of external devices – electrocardiography (ECG) devices, respiration sensors, microphone, electronics of the MR system etc. – using various channels for data transmission (analog, digital, optical fibers), all connected to a server through a universal serial bus (USB) hub. The software is based on a flexible client–server architecture, allowing real‐time processing pipelines to be configured and executed. Communication protocols and data formats are proposed, in particular for transferring the external device data to an open‐source reconstruction software (Gadgetron), for online image reconstruction using external physiological data. The system performance is evaluated in terms of accuracy of the recorded signals and delays involved in the real‐time processing tasks. Its flexibility is shown with various applications. Results: The real‐time system had low delays and jitters (on the order of 1 ms). Example MRI applications using external devices included: prospectively gated cardiac cine imaging, multi‐modal acquisition of the vocal tract (image, sound, and respiration) and online image reconstruction with nonrigid motion correction. Conclusion: The performance of the system and its versatile architecture make it suitable for a wide range of MRI applications requiring online or offline use of external device data. [ABSTRACT FROM AUTHOR]

Fricatives are a class of noisy speech sounds that are produced by forming partial constriction in the vocal tract. As a result, they have dominant high-frequency contents. Difficulty in speech production could lead to the production of fricatives with a place of constriction different from the actual. Automatic detection of fricatives helps in identifying the fricative regions and modifying the speech segment in that region. It also finds applications in designing hearing aids where frequency lowering is customary. Recent developments in speech processing make use of artificial neural networks rather than the traditional rule-based approach. However, it is challenging as it demands huge labeled data. Unsupervised approach can overcome the laborious labeling task. Auto resonance networks are one choice for unsupervised approach. Recently, auto resonance networks have been used in classification problems. This work proposes an unsupervised approach for fricative detection using auto resonance networks. A system is built to detect the fricatives in both controlled speech and pathological speech. The system is tested using the standard TIMIT database for controlled speech and TORGO database for pathological speech utterances. The results are compared with another standard unsupervised neural network approach namely, Self Organizing Maps. [ABSTRACT FROM AUTHOR]

• The study determines the main articulatory variations related to formant variations. • Articulatory components corresponding to formant variations were obtained. • Inter-speaker variability was qualitatively and quantitatively analysed. • The relationship between inter-speaker variability and morphology was determined. • Articulatory variations are slightly driven by palate shape and pharyngeal height. Vowels are articulatorily characterised by the shape of the vocal tract and acoustically by their three lowest formants. The relationship between formant variations and articulatory variations is well documented. This study addresses the opposite problem: describing the main articulatory variations associated with the variations of single formants. A data-driven modelling-based approach was chosen for this purpose. Midsagittal vocal tract contours from the glottis to the lips for 532 vowels from 41 speakers of three different languages were obtained from MRI data. Corresponding formant values were obtained by acoustic modelling. For each speaker, linear regressions of the contours on the formant values were performed. It led to five articulatory components, characterising the vocal tract variations associated with variations of the first three formants and their differences. Inter-speaker variability was analysed by applying principal components analysis on the components in a second level of modelling. A correlation analysis of the resulting inter-speaker components with morphological features was performed to determine whether a speaker's strategy could be driven by the morphology. Results show that the palate shape and the vertical pharyngeal height, related to the male–female difference, have a small influence on the speaker's strategy. Associated Matlab code is publicly available. [ABSTRACT FROM AUTHOR]

Background: Purpose Playing wind instruments is a strenuous task on the larynx, predisposing players to voice disorders. Aim of the Work: This study aims to evaluate potential vocal symptoms and vocal tract alterations in professional wind instrumentalists. Patients and Methods: Methods In this cross-sectional study, 26 male military subjects were interviewed, completed the voice handicap index (VHI)-10 questionnaire, and subjected to auditory-perceptual assessment, neck examination, rigid laryngostroboscopy and flexible nasofiberoscopy both before and during instrument playing. Results: All participants had vocal fatigue symptoms, around onequarter complained of voice change, one-quarter complained of shortness of breath while or after performing, and one-third complained of neck symptoms. The average score of VHI-10 was 16.266.5, and approximately three-quarters of participants scored above the cut-off point. There were no significant correlations between age, years of instrument playing, average hours of daily practice, and VHI-10. Participants with neck symptoms had significantly higher VHI-10 scores. Those (around one-fifth) with an external neck swelling during Valsalva maneuver had a significantly higher VHI-10 score. Dysphonia, mainly mild and of strained, leaky quality, was detected in almost one-third of participants. While the instrument was being played, the vocal folds were somewhat adducted, and the vocal tract became more compressed as the task became more demanding. The most frequent observations in the vocal tract examination were hyperemia of the vocal folds or all over the laryngeal and pharyngeal mucosa, excessive secretions over the vocal folds, signs of hyperadduction, arytenoid edema, and phonatory waste. Conclusion and Recommendations: Wind instrumentalists frequently experience voice disorders, which necessitate further care and investigation. [ABSTRACT FROM AUTHOR]

Simple Summary: Whether a vocalization is emitted though the mouth or nose impacts on its acoustic shape through specific vocal tract resonances. In human language, nasalized compared to oral vowels can change the meaning of words. African elephants mainly use low-frequency rumbles to communicate and can utter them either through the mouth or trunk. In this study, we used an acoustic camera to visualize the sound emission of rumbles in Asian elephants, which have been studied considerably less than African elephants. We recorded nine captive female Asian elephants and analyzed the acoustic structure of 203 calls. We found that most rumbles (64%) were emitted through the trunk, 21% through the mouth, and surprisingly, 13% simultaneously through the mouth and trunk. Some of the rumbles were combined with orally emitted roars. The nasal rumbles concentrated most spectral energy in lower frequencies, whereas the oral and mixed rumbles showed a broader spectral energy distribution and concentration in higher frequencies, and were louder. The roars were the loudest, broadest and highest in frequency. This study is the first to demonstrate coupled oral and nasal emission in a non–human animal, thereby setting an important framework to study the functions of this acoustic variability in elephant communication and the evolution of vocal flexibility across species. Sound production mechanisms set the parameter space available for transmitting biologically relevant information in vocal signals. Low–frequency rumbles play a crucial role in coordinating social interactions in elephants' complex fission–fusion societies. By emitting rumbles through either the oral or the three-times longer nasal vocal tract, African elephants alter their spectral shape significantly. In this study, we used an acoustic camera to visualize the sound emission of rumbles in Asian elephants, which have received far less research attention than African elephants. We recorded nine adult captive females and analyzed the spectral parameters of 203 calls, including vocal tract resonances (formants). We found that the majority of rumbles (64%) were nasally emitted, 21% orally, and 13% simultaneously through the mouth and trunk, demonstrating velopharyngeal coupling. Some of the rumbles were combined with orally emitted roars. The nasal rumbles concentrated most spectral energy in lower frequencies exhibiting two formants, whereas the oral and mixed rumbles contained higher formants, higher spectral energy concentrations and were louder. The roars were the loudest, highest and broadest in frequency. This study is the first to demonstrate velopharyngeal coupling in a non-human animal. Our findings provide a foundation for future research into the adaptive functions of the elephant acoustic variability for information coding, localizability or sound transmission, as well as vocal flexibility across species. [ABSTRACT FROM AUTHOR]

Pitch estimation is widely used in speech and audio signal processing. However, the current methods of modeling harmonic structure used for pitch estimation cannot always match the harmonic distribution of actual signals. Due to the structure of vocal tract, the acoustic nature of musical equipment, and the spectrum leakage issue, speech and audio signals' harmonic frequencies often slightly deviate from the integer multiple of the pitch. This paper starts with the summation of residual harmonics (SRH) method and makes two main modifications. First, the spectral peak position constraint of strict integer multiple is modified to allow slight deviation, which benefits capturing harmonics. Second, a main pitch segment extension scheme with low computational cost feature is proposed to utilize the smooth prior of pitch more efficiently. Besides, the pitch segment extension scheme is also integrated into the SRH method's voiced/unvoiced decision to reduce short-term errors. Accuracy comparison experiments with ten pitch estimation methods show that the proposed method has better overall accuracy and robustness. Time cost experiments show that the time cost of the proposed method reduces to around 1/8 of the state-of-the-art fast NLS method on the experimental computer. [ABSTRACT FROM AUTHOR]

Formants in speech signals are easily identified, largely because formants are defined to be local maxima in the wideband sound spectrum. Sadly, this is not what is of most interest in analyzing speech; instead, resonances of the vocal tract are of interest, and they are much harder to measure. Klatt [(1986). in Proceedings of the Montreal Satellite Symposium on Speech Recognition, 12th International Congress on Acoustics, edited by P. Mermelstein (Canadian Acoustical Society, Montreal), pp. 5–7] showed that estimates of resonances are biased by harmonics while the human ear is not. Several analysis techniques placed the formant closer to a strong harmonic than to the center of the resonance. This "harmonic attraction" can persist with newer algorithms and in hand measurements, and systematic errors can persist even in large corpora. Research has shown that the reassigned spectrogram is less subject to these errors than linear predictive coding and similar measures, but it has not been satisfactorily automated, making its wider use unrealistic. Pending better techniques, the recommendations are (1) acknowledge limitations of current analyses regarding influence of F0 and limits on granularity, (2) report settings more fully, (3) justify settings chosen, and (4) examine the pattern of F0 vs F1 for possible harmonic bias. [ABSTRACT FROM AUTHOR]

Animal vocalizations convey important information about the emitter, including sex, age, biological quality, and emotional state. Early on, Darwin proposed that sex differences in auditory signals and vocalizations were driven by sexual selection mechanisms. In humans, studies on the association between male voice attributes and physical formidability have thus far reported mixed results. Hence, with a view to furthering our understanding of the role of human voice in advertising physical formidability, we sought to identify acoustic attributes of male voices associated with physical formidability proxies. Mean fundamental frequency (F0), formant dispersion (Df), formant position (Pf), and vocal tract length (VTL) data from a sample of 101 male voices was analyzed for potential associations with height, weight, and maximal handgrip strength (HGS). F0 correlated negatively with HGS; Pf showed negative correlations with HGS, height and weight, whereas VTL positively correlated with HGS, height and weight. All zero-order correlations remained significant after controlling for false discovery rate (FDR) with the Benjamini-Hochberg method. After controlling for height and weight--and controlling for FDR--the correlation between F0 and HGS remained significant. In addition, to evaluate the ability of human male voices to advertise physical formidability to potential mates, 151 heterosexual female participants rated the voices of the 10 strongest and the 10 weakest males from the original sample for perceived physical strength, and given that physical strength is a desirable attribute in male partners, perceived attractiveness. Generalized linear mixed model analyses--which allow for generalization of inferences to other samples of both raters and targets--failed to support a significant association of perceived strength or attractiveness from voices alone and actual physical strength. These results add to the growing body of work on the role of human voices in conveying relevant biological information. [ABSTRACT FROM AUTHOR]

Voice therapy often emphasizes vibratory sensations in the front part of the vocal tract during phonation to improve vocal efficiency. It remains unclear what laryngeal and vocal tract adjustments are elicited in speakers by this emphasis on oral vibratory sensations. Using a three-dimensional phonation model, this study aims to identify laryngeal and epilaryngeal adjustments that might produce maximal oral vibratory sensations during phonation, as quantified by the oral sound pressure level (SPL), and thus are likely to be elicited in voice therapy at different semi-occluded vocal tract configurations. Results show that maximum oral SPL occurs at intermediate vocal fold adduction configurations characterized by a trade-off between glottal gap and vocal fold vertical thickness. Epilaryngeal tube narrowing further increases the oral SPL in an open vocal tract, but has little effect on oral SPL in semi-occluded vocal tracts. Laryngeal and epilaryngeal configurations producing the maximum oral SPL generally have lower peak vocal fold contact pressure when producing a target output SPL. These favorable configurations are more easily identified in open vocal tracts than semi-occluded vocal tracts. However, semi-occlusion increases both the mean and dynamic oral pressure, which may familiarize speakers with oral vibratory sensations and facilitate adoption of favorable laryngeal configurations. [ABSTRACT FROM AUTHOR]

The avian bill is finely adjusted to foraging ecology and, as part of the vocal tract, it may also affect sexual signals such as songs. Acoustic theory predicts that larger bills lower the resonant frequency of vocal tracts, allowing larger-billed species to emphasize lower sound frequencies. Theory also predicts that identical changes in bill gape allow singing over a wider frequency bandwidth in larger-billed species. We tested these associations between bill size and sound frequencies of song, controlling for body mass, across ca. 1000 taxonomically-diverse passerines. Phylogenetically informed analyses indicated that both bill and body sizes are negatively related to the sound frequency of songs, with additive effects of similar strength. Analyses of reduced datasets, to decrease bill-body size associations, indicated that the effect of bill size remains identical and is thus not an artefact of its covariation with body size. Sound frequency bandwidth was only related to body size but not bill size, perhaps because large bills may allow greater modulation of frequency but also hinder fast bill movement. Since the bill has a major role explaining species differences in birdsong sound frequency, it can be a magic trait that promotes reproductive isolation as a consequence of ecological divergence. [ABSTRACT FROM AUTHOR]

Vocal characteristics are important cues to form social impressions. Previous studies indicated that men with masculine voices are perceived as engaging in higher rates of infidelity and being less committed to their relationship. In the current study, we examined how women in China perceive information regarding infidelity and relationship investment conveyed by the voices (voice pitch and vocal tract length) of males, and whether different vocal characteristics play a similar role in driving these impressions. In addition, we examined whether these perceptions are consistent in Chinese and English language contexts. The results indicated that women perceived men with more masculine voices (lower voice pitch and longer vocal tract length) as showing a lower likelihood of infidelity and higher relationship investment; further, women who preferred more masculine voices in long-term relationships, but not in short-term relationships, were more likely to perceive men with masculine voices as less likely to engage in infidelity and more likely to invest in their relationship. Moreover, the participants formed very similar impressions irrespective of whether the voices spoke native (Chinese) or foreign (English) languages. These results provide new evidence for the role of the voice in women's choices in selecting long-term partners. [ABSTRACT FROM AUTHOR]

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In MR (mixed reality) environments, visual searches are often used for search and localization missions. There are some problems with search and localization technologies, such as a limited field of view and information overload. They are unable to satisfy the need for the rapid and precise location of specific flying objects in a group of air and space targets under modern air and space situational requirements. They lead to inefficient interactions throughout the mission process. A human being's decision and judgment will be affected by inefficient interactions. Based on this problem, we carried out a multimodal optimization study on the use of an auditory-assisted visual search for localization in an MR environment. In the spatial–spherical coordinate system, the target flight object position is uniquely determined by the height h, distance r, and azimuth θ. Therefore, there is an urgent need to study the cross-modal connections between the auditory elements and these three coordinates based on a visual search. In this paper, an experiment was designed to study the correlation between auditory intuitive perception and vision and the cognitive induction mechanism. The experiment included the three cross-modal mappings of pitch–height, volume–distance, and vocal tract alternation–spatial direction. The research conclusions are as follows: (1) Visual cognition is induced by high, medium, and low pitches to be biased towards the high, medium, and low spatial regions of the visual space. (2) Visual cognition is induced by loud, medium, and low volumes to be biased towards the near, middle, and far spatial regions of the visual space. (3) Based on the HRTF application, the vocal track alternation scheme is expected to significantly improve the efficiency of visual interactions. Visual cognition is induced by left short sounds, right short sounds, left short and long sounds, and right short and long sounds to be biased towards the left, right, left-rear, and right-rear directions of visual space. (4) The cognitive load of search and localization technologies is significantly reduced by incorporating auditory factors. In addition, the efficiency and effect of the accurate search and positioning of space-flying objects have been greatly improved. The above findings can be applied to the research on various types of target search and localization technologies in an MR environment and can provide a theoretical basis for the subsequent study of spatial information perception and cognitive induction mechanisms in an MR environment with visual–auditory coupling. [ABSTRACT FROM AUTHOR]

Dysarthria is an early symptom of Parkinson's disease (PD) which has been proposed for detection and monitoring of the disease with potential for telehealth. However, with inherent differences between voices of different people, computerized analysis have not demonstrated high performance that is consistent for different datasets. The aim of this study was to improve the performance in detecting PD voices and test this with different datasets. This study has investigated the effectiveness of three groups of phoneme parameters, i.e. voice intensity variation, perturbation of glottal vibration, and apparent vocal tract length (VTL) for differentiating people with PD from healthy subjects using two public databases. The parameters were extracted from five sustained phonemes; /a/, /e/, /i/, /o/, and /u/, recorded from 50 PD patients and 50 healthy subjects of PC-GITA dataset. The features were statistically investigated, and then classified using Support Vector Machine (SVM). This was repeated on Viswanathan dataset with smartphone-based recordings of /a/, /o/, and /m/ of 24 PD and 22 age-matched healthy people. VTL parameters gave the highest difference between voices of people with PD and healthy subjects; classification accuracy with the five vowels of PC-GITA dataset was 84.3% while the accuracy for other features was between 54% and 69.2%. The accuracy for Viswanathan's dataset was 96.0%. This study has demonstrated that VTL obtained from the recording of phonemes using smartphone can accurately identify people with PD. The analysis was fully computerized and automated, and this has the potential for telehealth diagnosis for PD. [ABSTRACT FROM AUTHOR]

Articulatory speech synthesis requires generating realistic vocal tract shapes from the sequence of phonemes to be articulated. This work proposes the first model trained from rt-MRI films to automatically predict all of the vocal tract articulators' contours. The data are the contours tracked in the rt-MRI database recorded for one speaker. Those contours were exploited to train an encoder–decoder network to map the sequence of phonemes and their durations to the exact gestures performed by the speaker. Different from other works, all the individual articulator contours are predicted separately, allowing the investigation of their interactions. We measure four tract variables closely coupled with critical articulators and observe their variations over time. The test demonstrates that our model can produce high-quality shapes of the complete vocal tract with a good correlation between the predicted and the target variables observed in rt-MRI films, even though the tract variables are not included in the optimization procedure. [ABSTRACT FROM AUTHOR]

The article discusses research which estimated the vocal tract length of wild male southern elephant seal during their normal vocalization behavior, using two dimensional (2D) videogrammetry. Topics covered include the feasibility of noninvasive vocal tract measurement in wild male southern elephant seals, the repeatability of several vocal tract measures and the correlation between them, and the association between the vocal tract and the structural phenotype that may constrain it.

The perceived pitch of human voices is highly correlated with the fundamental frequency (f0) of the laryngeal source, which is determined largely by the length and mass of the vocal folds. The vocal folds are larger in adult males than in adult females, and men's voices consequently have a lower pitch than women's. The length of the supralaryngeal vocal tract (vocal-tract length; VTL) affects the resonant frequencies (formants) of speech which characterize the timbre of the voice. Men's longer vocal tracts produce lower frequency, and less dispersed, formants than women's shorter vocal tracts. Pitch and timbre combine to influence the perception of speaker characteristics such as size and age. Together, they can be used to categorize speaker sex with almost perfect accuracy. While it is known that domestic dogs can match a voice to a person of the same sex, there has been no investigation into whether dogs are sensitive to the correlation between pitch and timbre. We recorded a female voice giving three commands ('Sit', 'Lay down', 'Come here'), and manipulated the recordings to lower the fundamental frequency (thus lowering pitch), increase simulated VTL (hence affecting timbre), or both (synthesized adult male voice). Dogs responded to the original adult female and synthesized adult male voices equivalently. Their tendency to obey the commands was, however, reduced when either pitch or timbre was manipulated alone. These results suggest that dogs are sensitive to both the pitch and timbre of human voices, and that they learn about the natural covariation of these perceptual attributes. [ABSTRACT FROM AUTHOR]

This paper is part of a special issue on Music Technology. Accurate estimation of glottal wave is an important method for singing voice analysis via voicing patterns. In this paper, an optimising method is proposed for automatic determination of vocal tract linear prediction analysis order that follows the specific situation of different voicing scenes based on Iterative Adaptive Inverse Filtering (IAIF) aiming at getting a more accurate glottal wave from speech or singing voice signal in a non‐invasive way. In comparison with existing methods that use fixed experience order, the proposed method can achieve up to 8.41% improvement in correlation coefficient with the real glottal wave. [ABSTRACT FROM AUTHOR]

Stuttering is a neurodevelopmental speech disorder wherein people suffer from disfluency in speech generation. Recent research has applied machine learning and deep learning approaches to stuttering disfluency recognition and classification. However, these studies have focussed on small datasets, generated by a limited number of speakers and within specific tasks, such as reading. This paper rigorously investigates the effective use of eight well-known machine learning classifiers, on two publicly available datasets (FluencyBank and SEP-28k) to automatically detect stuttering disfluency using multiple objective metrics, i.e. prediction accuracy, recall, precision, F1-score, and AUC measures. Our experimental results on the two datasets show that the Random Forest classifier achieves the best performance, with an accuracy of 50.3% and 50.35%, a recall of 50% and 42%, a precision of 42% and 46%, and an F1 score of 42% and 34%, against the FluencyBank and SEP-28K datasets, respectively. Moreover, we show that the machine learning-based approaches may not be effective in accurate stuttering disfluency evaluation, due to diverse variations in speech rate, and differences in vocal tracts between children and adults. We argue that the use of deep learning approaches and Automatic Speech Recognition (ASR) with language models may improve outcomes, specifically for large scale and imbalanced datasets. [ABSTRACT FROM AUTHOR]

This work presents the analysis and classification of emotional speech signals using a novel technique, variational mode decomposition on recorded speech samples. The vocal tract changes its characteristics during production of speech signals at various emotions. Variational mode decomposition, technique decomposes the speech signal into various modes. The input speech frames are divided into five intrinsic mode functions or modes. Statistical parameters like interquartile range, median absolute deviation and energy of the mode functions are extracted and mean instantaneous frequency of each mode function is also calculated and considered as features in speech emotion recognition. Extracted features are used to classify emotional speech signals using support vector machine with linear functions as kernels. This work provides recognition rate, with an accuracy of 31.2% using only mode center frequency and its statistical parameters as features. Adding of Mel frequency cepstral coefficients of speech as a feature to the mode center frequency and its statistical parameters, increases the accuracy in recognition by 12.6%. As the feature set is further added with the spectral statistical parameters of speech as features, which preserve the emotional content in frequency domain, 61.2% of accuracy is achieved in recognizing emotions using support vector machines with radial basis kernels. Mode center frequency and its statistical features contribute 31.2% in recognizing emotions from speech signals. This method provides an accuracy of 85.81% and 69.13% respectively, in recognizing two and four emotions. This particular method provides better accuracy with an increase of 5% in recognition rate compared to bidirectional long short-term memory convolutional capsule neural network proposed by Jalal et al., in recognizing eight emotions, providing better results than multitasking feature selection and convolutional neural networks methods. [ABSTRACT FROM AUTHOR]

While Grawunder et al. do not report I f i SB 0 sb values of chimpanzee screams from which formants are estimated, measurements for scream climaxes have elsewhere been reported to be as high as I f i SB 0 sb > 1,500 Hz (Mitani et al., [4]). Indeed, most F SB 1 sb and F SB 2 sb values reported for scream calls (Grawunder et al., [3], p. 9) follow an apparent 1:2 ratio, suggesting that frequencies of two lower-spectrum partials were interpreted as formants. Analysis of nonhuman, great ape vocal behavior may provide insight into the evolution of human speech. [Extracted from the article]

Recent studies have determined that the number of respiratory droplets expelled during a short duration of speech can be comparable to that of a cough. Although speaking is typically modeled as a horizontal jet, recent experimental work has shown that there are large angular variations when fricative sounds are produced. To investigate this, two-dimensional vocal tract geometries for a labiodental fricative, [f] and a dental fricative, [ θ ] were constructed based on magnetic resonance imaging (MRI) during these intonations. Two-dimensional ANSYS-Fluent simulations were performed to investigate the expiratory airflow from the geometries, which showed chaotic unsteady airflow trajectories with maximum velocities ranging from 20 to 40 m/s and jet trajectory angles varying between ± 60 °. The simulations highlight the variabilities of the expirated airflow trajectories as a function of the type of utterance, speech loudness, size of the mouth opening, and tongue shape. Copyright © 2022 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

European Portuguese (EP) is characterized by a large number of nasals encompassing five phonemic nasal vowels. One notable characteristic of these sounds is their dynamic nature, involving both oral and nasal gestures, which makes their study and characterization challenging. The study of nasal vowels, in particular, has been addressed using a wide range of technologies: early descriptions were based on acoustics and nasalance, later expanded with articulatory data obtained from EMA and real-time magnetic resonance (RT-MRI). While providing important results, these studies were limited by the discrete nature of the EMA-pellets, providing only a small grasp of the vocal tract; by the small time resolution of the MRI data; and by the small number of speakers. To tackle these limitations, and to take advantage of recent advances in RT-MRI allowing 50 fps, novel articulatory data has been acquired for 11 EP speakers. The work presented here explores the capabilities of recently proposed data-driven approaches to model articulatory data extracted from RT-MRI to assess their suitability for investigating the dynamic characteristics of nasal vowels. To this end, we explore vocal tract configurations over time, along with the coordination of velum and lip aperture in oral and nasal bilabial contexts for nasal vowels and oral congeners. Overall, the results show that both generalized additive mixed models (GAMMs) and functional linear mixed models (FLMMs) provide an elegant approach to tackle the data from multiple speakers. More specifically, we found oro-pharyngeal differences in the tongue configurations for low and mid nasal vowels: vowel track aperture was larger in the pharyngeal and smaller in the palatal region for the three non-high nasal vowels, providing evidence of a raised and more advanced tongue position of the nasal vowels. Even though this work is aimed at exploring the applicability of the methods, the outcomes already highlight interesting data for the dynamic characterization of EP nasal vowels. [ABSTRACT FROM AUTHOR]

Gender affirmation laryngeal and voice surgeries are components of "voice-lift" or cosmetic voice surgeries. Feminization surgery can modify vocal folds (fundamental frequency [Fo]) and vocal tract (resonance frequency). For increased pitch, vocal folds should be shorter, thinner, and tighter. Cricothyroid approximation (CTA) surgery increases tension of the vocal folds. Endoscopic procedures for pitch raising are done by shortening the length and reducing mass of vocal folds. This shortening is achieved by surgically creating anterior glottic web. Comparing the results of various open and endoscopic surgical techniques, fundamental frequency (Fo) is raised maximally and remains stable after GL as compared with CTA. [ABSTRACT FROM AUTHOR]

Purpose: The authors aim to review available reports on the potential effects of masks on voice and speech parameters. Methods: A literature search was conducted using MEDLINE and Google Scholar databases through July 2021. Several targeted populations, mask scenarios and methodologies were approached. The assessed voice parameters were divided into self-reported, acoustic and aerodynamic. Results: It was observed that the wearing of a face mask has been shown to induce several changes in voice parameters: (1) self-reported—significantly increased vocal effort and fatigue, increased vocal tract discomfort and increased values of voice handicap index (VHI) were observed; (2) acoustics—increased voice intensity, altered formants frequency (F2 and F3) with no changes in fundamental frequency, increased harmonics-to-noise ratio (HNR) and increased mean spectral values in high-frequency levels (1000–8000 Hz), especially with KN95 mask; (3) aerodynamics—maximum phonatory time was assessed in only two reports, and showed no alterations. Conclusion: Despite the different populations, mask-type scenarios and methodologies described by each study, the results of this review outline the significant changes in voice characteristics with the use of face masks. Wearing a mask shows to increase the perception of vocal effort and an alteration of the vocal tract length and speech articulatory movements, leading to spectral sound changes, impaired communication and perception. Studies analyzing the effect of masks on voice aerodynamics are lacking. Further research is required to study the long-term effects of face masks on the potential development of voice pathology. [ABSTRACT FROM AUTHOR]

Over a range roughly C5–C6, sopranos usually tune their first vocal tract resonance (R1) to the fundamental frequency (fo) of the note sung: R1:fo tuning. Those who sing well above C6 usually adjust their second vocal tract resonance (R2) and use R2:fo tuning. This study investigated these questions: Can singers quickly learn R2:fo tuning when given suitable feedback? Can they subsequently use this tuning without feedback? And finally, if so, does this assist their singing in the high range? New computer software for the technique of resonance estimation by broadband excitation at the lips was used to provide real-time visual feedback on fo and vocal tract resonances. Eight sopranos participated. In a one-hour session, they practised adjusting R2 whilst miming (i.e. without phonating), and then during singing. Six sopranos learned to tune R2 over a range of several semi-tones, when feedback was present. This achievement did not immediately extend their singing range. When the feedback was removed, two sopranos spontaneously used R2:fo tuning at the top of their range above C6. With only one hour of training, singers can learn to adjust their vocal tract shape for R2:fo tuning when provided with visual feedback. One additional participant who spent considerable time with the software, acquired greater skill at R2:fo tuning and was able to extend her singing range. A simple version of the hardware used can be assembled using basic equipment and the software is available online. [ABSTRACT FROM AUTHOR]

While influential works since the 1970s have widely assumed that imitation is an innate skill in both human and non-human primate neonates, recent empirical studies and meta-analyses have challenged this view, indicating other forms of reward-based learning as relevant factors in the development of social behavior. The visual input translation into matching motor output that underlies imitation abilities instead seems to develop along with social interactions and sensorimotor experience during infancy and childhood. Recently, a new visual stream has been identified in both human and non-human primate brains, updating the dual visual stream model. This third pathway is thought to be specialized for dynamics aspects of social perceptions such as eye-gaze, facial expression and crucially for audio-visual integration of speech. Here, we review empirical studies addressing an understudied but crucial aspect of speech and communication, namely the processing of visual orofacial cues (i.e., the perception of a speaker's lips and tongue movements) and its integration with vocal auditory cues. Along this review, we offer new insights from our understanding of speech as the product of evolution and development of a rhythmic and multimodal organization of sensorimotor brain networks, supporting volitional motor control of the upper vocal tract and audio-visual voices-faces integration. [ABSTRACT FROM AUTHOR]

We present a neural implementation of the all pass warp (APW) previously used for vocal tract length normalisation. This includes an efficient back-propagation, which can easily be integrated in modern neural network frameworks. The APW offers a low-dimensional control to alter the spectrum, which by design generalises over different speakers. We investigate the APW in two tasks required for future dialogue or translation agents, and provide a fairly thorough literature review for both: (1) Zero-shot speaker adaptation to allow keeping the source speaker identity with very small amounts of data. Experiments show increased speaker similarity and prove that the APW increases the generalisability of a multi-speaker model. (2) Emotional speech synthesis to translate or produce affective cues. To the best of our knowledge this is the first attempt on emotional speech synthesis with an APW. While the APW is not able to increase expressiveness or audio quality, our analysis shows that the warping correlates with the level of valence in the emotion. This work should enable future research on emotion translation during machine translation. • Investigate a neural back-propagatable all pass warp layer in text-to-speech. • The technique is inspired by vocal tract length normalisation. • Improved speaker similarity on zero-shot speaker adaptation. • Predicted warping correlates with valence in emotional speech synthesis. [ABSTRACT FROM AUTHOR]

To demonstrate physiological changing of vocal tract's structures during overtone singing with commercial magnetic resonance imaging (MRI) Fast Imaging Employing Steady State Acquisition (FIESTA) dynamic sequence. A 1.5 T MRI with a 16 channel head-and-neck coil and a FIESTA sequence were used. A temporal resolution of 0.155 sec (7 image/s). A single professional singer was studied. The MR acquisition is made while the singer performed a predetermined singing sequence. Three different overtone singing techniques were examined (L-technique, J-technique, and NG technique) and one effect (Ezengileer) applied to L-technique. For each overtone technique we evaluated MRI movement of lips, tongue, velopharyngeal closure, and relationship among tongue and pharyngeal posterior wall/soft palate. To cancel the noise over-imposed, the dynamic MRI was subsequently dubbed in studio with the audio of the preset overtone sing. Dubbed MR images were analyzed with an Overtone Analyzer Software and different sound frequencies were identified and pointed out as colored lines. This study shows that different overtone techniques are related to a specific conformation of tongue, lips, soft and hard palate and motion's relation changing between them. Only a correct conformation of vocal tract's structure allows resonance and so to hear desired fundamental and harmonic pitch in overtone singing. The preliminary data of our study demonstrates that FIESTA dynamic MRI sequence can be used to depict changing of position of vocal tract's structure in overtone singing techniques with a good temporal and anatomic resolution. [ABSTRACT FROM AUTHOR]

Acoustic correlates of consonantal place of articulation are numerous and varied. Burst information, onset spectra, and formant transition motion have all been implicated as the significant cues for consonant place of articulation within each labial, alveolar, and velar place category. The main purpose of this study was to investigate the transition rate of a vowel formant, which was the ascending or descending slope of the formant in CV syllables. Therefore, this analysis offered additional insights to the role of F2 transition at the onset and mid-points when serving as predictor variables. The results showed that F1 vowel transitions had an ascending slope. Increasing the value of F1 vowel transition after the releases of labial, alveolar, and velar consonants was an acoustic clue to the opening of the oral cavity and absence of obstruction/closure in the vocal tract. The statistical analyses demonstrated that only in the vowels [o, u, æ], there was a significant difference between the second formant frequencies at the two onset and the mid-points of the transition after all coronals, labials, and velars. The difference between these two variables was not significant in the other cases. [ABSTRACT FROM AUTHOR]

Aim: The aim of the study was to analyze the impact of the COVID-19 pandemic and the related change of the teaching mode from stationary to distance learning on the severity of voice-related ailments among teachers. Materials and methods: A questionnaire survey of teachers was conducted to assess voice disorders during stationary and remote work using the Vocal Tract Discomfort (VTDs) scale and Numeric Rating Scale (NRS), and the respondents' subjective feelings were assessed. Demographic and environmental factors associated with voice work were examined. Data on sickness absence, which were obtained from the "Health Needs Maps 2020" Ministry of Health's, were also analyzed. Responses were subjected to statistical analysis. A P-value level below 0.05 was considered statistically significant. Results: 128 teachers participated in the survey. The overall assessment of voice disorders using VTDs and NRS scales showed no statistically significant differences for complaints between stationary and remote work. Detailed analysis revealed more severe voice disorders in teachers working more than 6 months remotely (P = 0.049) and having more than 20 lessons per week (P = 0.012). Subjective assessment confirmed a significantly lower percentage of teachers reporting voice disorders when working remotely compared to stationary (P = 0.043). This resulted in less sickness absence and a 40% decrease in sick leave related to voice disorders in 2020 compared to 2019. Conclusions: During the remote learning period of the COVID-19 pandemic, teachers reported lower severity of voice disorders and this influenced the reduction of sickness absences. There were no statistically significant differences in voice complaints as assessed by VTDs and NRS scales for both teaching modes. Several factors affecting the severity of vocal tract disorders were identified -- the number of class hours per week (>20) for stationary teaching and a long period of remote teaching (>6 months). [ABSTRACT FROM AUTHOR]

Modeling speech production and speech articulation is still an evolving research topic. Some current core questions are: What is the underlying (neural) organization for controlling speech articulation? How to model speech articulators like lips and tongue and their movements in an efficient but also biologically realistic way? How to develop high-quality articulatory-acoustic models leading to high-quality articulatory speech synthesis? Thus, on the one hand computer-modeling will help us to unfold underlying biological as well as acoustic-articulatory concepts of speech production and on the other hand further modeling efforts will help us to reach the goal of high-quality articulatory-acoustic speech synthesis based on more detailed knowledge on vocal tract acoustics and speech articulation. Currently, articulatory models are not able to reach the quality level of corpus-based speech synthesis. Moreover, biomechanical and neuromuscular based approaches are complex and still not usable for sentence-level speech synthesis. This paper lists many computer-implemented articulatory models and provides criteria for dividing articulatory models in different categories. A recent major research question, i.e., how to control articulatory models in a neurobiologically adequate manner is discussed in detail. It can be concluded that there is a strong need to further developing articulatory-acoustic models in order to test quantitative neurobiologically based control concepts for speech articulation as well as to uncover the remaining details in human articulatory and acoustic signal generation. Furthermore, these efforts may help us to approach the goal of establishing high-quality articulatory-acoustic as well as neurobiologically grounded speech synthesis.

The human voice carries socially relevant information such as how authoritative, dominant, and attractive the speaker sounds. However, some speakers may be able to manipulate listeners by modulating the shape and size of their vocal tract to exaggerate certain characteristics of their voice. We analysed the veridical size of speakers' vocal tracts using real-time magnetic resonance imaging as they volitionally modulated their voice to sound larger or smaller, corresponding changes to the size implied by the acoustics of their voice, and their influence over the perceptions of listeners. Individual differences in this ability were marked, spanning from nearly incapable to nearly perfect vocal modulation, and was consistent across modalities of measurement. Further research is needed to determine whether speakers who are effective at vocal size exaggeration are better able to manipulate their social environment, and whether this variation is an inherited quality of the individual, or the result of life experiences such as vocal training. [ABSTRACT FROM AUTHOR]