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Obtaining real-world multi-channel speech recordings is expensive and time-consuming. Therefore, multi-channel recordings are often artificially generated by convolving existing monaural speech recordings with simulated Room Impulse Responses (RIRs) from a so-called shoebox room [1] for stationary (not moving) speakers. Far-field speech processing for home automation or smart assistants have to cope with moving speakers in reverberant environments. With this dataset, we aim to support the generation of realistic speech data by providing multiple directional RIRs along a fine grid of locations in a real room. We provide directional RIR recordings for a classroom and a large corridor. These RIRs can be used to simulate moving speakers by generating random trajectories on that grid, and quantize the trajectories along the grid points. For each matching grid point, the monaural speech recording can be convolved with the RIR at this grid point. Then, the spatialized recording can be compiled using the overlap-add method for each grid point [2]. An example is provided with the data.

The neuronal signatures of sensory and cognitive load provide access to brain activities related to complex listening situations. Sensory and cognitive loads are typically reflected in measures like response time (RT) and event-related potentials (ERPs) components. It's, however, strenuous to distinguish the underlying brain processes solely from these measures. In this study, along with RT- and ERP-analysis, we performed time-frequency analysis and source localization of oscillatory activity in participants performing two different auditory tasks with varying degrees of complexity and related them to sensory and cognitive load. We studied neuronal oscillatory activity in both periods before the behavioral response (pre-response) and after it (post-response). Robust oscillatory activities were found in both periods and were differentially affected by sensory and cognitive load. Oscillatory activity under sensory load was characterized by decrease in pre-response (early) theta activity and increased alpha activity. Oscillatory activity under cognitive load was characterized by increased theta activity, mainly in post-response (late) time. Furthermore, source localization revealed specific brain regions responsible for processing these loads, such as temporal and frontal lobe, cingulate cortex and precuneus. The results provide evidence that in complex listening situations, the brain processes sensory and cognitive loads differently. These neural processes have specific oscillatory signatures and are long lasting, extending beyond the behavioral response.

Eye gaze is a powerful ostensive cue in infant-caregiver interactions, with demonstrable effects on language acquisition. While the link between gaze following and later vocabulary is well-established, the effects of eye gaze on other aspects of language, such as speech processing, are less clear. In this EEG study, we examined the effects of the speaker’s eye gaze on ten-month-old infants’ neural tracking of naturalistic audiovisual speech, a marker for successful speech processing. Infants watched videos of a speaker telling stories, addressing the infant with direct or averted eye gaze. We assessed infants’ speech-brain coherence at stress (1–1.75 Hz) and syllable (2.5–3.5 Hz) rates, tested for differences in attention by comparing looking times and EEG theta power in the two conditions, and investigated whether neural tracking predicts later vocabulary. Our results showed that infants’ brains tracked the speech rhythm both at the stress and syllable rates, and that infants’ neural tracking at the syllable rate predicted later vocabulary. However, speech-brain coherence did not significantly differ between direct and averted gaze conditions and infants did not show greater attention to direct gaze. Overall, our results suggest significant neural tracking at ten months, related to vocabulary development, but not modulated by speaker’s gaze.

Background: Older adults process speech differently, but it is not yet clear how aging affects different levels of processing natural, continuous speech, both in terms of bottom-up acoustic analysis and top-down generation of linguistic-based predictions. We studied natural speech processing across the adult lifespan via electroencephalography (EEG) measurements of neural tracking.Goals: Our goals are to analyze the unique contribution of linguistic speech processing across the adult lifespan using natural speech, while controlling for the influence of acoustic processing. Moreover, we also studied acoustic processing across age. In particular, we focus on changes in spatial and temporal activation patterns in response to natural speech across the lifespan.Methods: 52 normal-hearing adults between 17 and 82 years of age listened to a naturally spoken story while the EEG signal was recorded. We investigated the effect of age on acoustic and linguistic processing of speech. Because age correlated with hearing capacity and measures of cognition, we investigated whether the observed age effect is mediated by these factors. Furthermore, we investigated whether there is an effect of age on hemisphere lateralization and on spatiotemporal patterns of the neural responses.Results: Our EEG results showed that linguistic speech processing declines with advancing age. Moreover, as age increased, the neural response latency to certain aspects of linguistic speech processing increased. Also acoustic neural tracking (NT) decreased with increasing age, which is at odds with the literature. In contrast to linguistic processing, older subjects showed shorter latencies for early acoustic responses to speech. No evidence was found for hemispheric lateralization in neither younger nor older adults during linguistic speech processing. Most of the observed aging effects on acoustic and linguistic processing were not explained by age-related decline in hearing capacity or cognition. However, our results suggest that the effect of decreasing linguistic neural tracking with advancing age at word-level is also partially due to an age-related decline in cognition than a robust effect of age.Conclusion: Spatial and temporal characteristics of the neural responses to continuous speech change across the adult lifespan for both acoustic and linguistic speech processing. These changes may be traces of structural and/or functional change that occurs with advancing age.

The ability to process speech in noise (SPiN) declines with age, with a detrimental impact on life quality. Music-making activities such as singing and playing a musical instrument have raised interest as potential prevention strategies for SPiN perception decline because of their positive impact on several brain system, especially the auditory system, which is critical for SPiN. However, the literature on the effect of musicianship on SPiN performance has yielded mixed results. By critically assessing the existing literature with a systematic review and a meta-analysis, we aim to provide a comprehensive portrait of the relationship between music-making activities and SPiN in different experimental conditions. 38/49 articles, most focusing on young adults, were included in the quantitative analysis. The results show a positive relationship between music-making activities and SPiN, with the strongest effects found in the most challenging listening conditions, and little to no effect in less challenging situations. This pattern of results supports the notion of a relative advantage for musicians on SPiN performance and clarify the scope of this effect. However, further studies, especially with older adults, using adequate randomization methods, are needed to extend the present conclusions and assess the potential for musical activities to be used to mitigate SPiN decline in seniors.

Brain asymmetries are hypothesized to reduce functional duplication and thus have evolutionary advantages. The goal of this study was to examine whether early brain lateralization contributes to skill development within the speech-language domain. To achieve this goal, 25 infants (2-13 months old) underwent behavioral language examination and fMRI during sleep while listening to forward and backward speech, and then were assessed on various language skills at 55-69 months old. We observed that infant functional lateralization of the superior temporal gyrus (STG) for forward > backward speech was associated with phonological, vocabulary, and expressive language skills 4 to 5 years later. However, we failed to observe that infant language skills or the anatomical lateralization of STG were related to subsequent language skills. Overall, our findings suggest that infant functional lateralization of STG for speech perception may scaffold subsequent language acquisition, supporting the hypothesis that functional hemisphere asymmetries are advantageous., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Age-related hearing loss is a highly prevalent condition, which manifests at both the auditory periphery and the brain. It leads to degraded auditory input, which needs to be repaired in order to achieve understanding of spoken language. It is still unclear how older adults with this condition draw on their neural resources to optimally process speech. By presenting interrupted speech to 26 healthy older adults with normal-for-age audiograms, this study investigated neural tracking of degraded auditory input. The electroencephalograms of the participants were recorded while they first listened to and then verbally repeated sentences interrupted by silence in varying interruption rates. Speech tracking was measured by inter-trial phase coherence in response to the stimuli. In interruption rates that corresponded to the theta frequency band, speech tracking was highly specific to the interruption rate and positively related to the understanding of interrupted speech. These results suggest that older adults’ brain activity optimizes through the tracking of stimulus characteristics, and that this tracking aids in processing an incomplete auditory stimulus. Further investigation of speech tracking as a candidate training mechanism to alleviate age-related hearing loss is thus encouraged.

How do humans excel at tracking the narrative of a particular speaker with a distracting noisy background? This feat places great demands on the collaboration between speech processing and goal-related regulatory functions. Here, we propose that separate subsystems with different cross-task dynamic activity properties and distinct functional purposes support goal-directed speech listening. We adopted a naturalistic dichotic speech listening paradigm in which listeners were instructed to attend to only one narrative from two competing inputs. Using functional magnetic resonance imaging with inter- and intra-subject correlation techniques, we discovered a dissociation in response consistency in temporal, parietal and frontal brain areas as the task demand varied. Specifically, some areas in the bilateral temporal cortex (SomMotB_Aud and TempPar) and lateral prefrontal cortex (DefaultB_PFCl and ContA_PFCl) always showed consistent activation across subjects and across scan runs, regardless of the task demand. In contrast, some areas in the parietal cortex (DefaultA_pCunPCC and ContC_pCun) responded reliably only when the task goal remained the same. These results suggested two dissociated functional neural networks that were independently validated by performing a data-driven clustering analysis of voxelwise functional connectivity patterns. A subsequent meta-analysis revealed distinct functional profiles for these two brain correlation maps. The different-task correlation map was strongly associated with language-related processes (e.g., listening, speech and sentences), whereas the same-task versus different-task correlation map was linked to self-referencing functions (e.g., default mode, theory of mind and autobiographical topics). Altogether, the three-pronged findings revealed two anatomically and functionally dissociated subsystems supporting goal-directed speech listening.

The GEMMA database consists of recordings of disyllabic words: vowel-consonant-vowel (VCV) for nongeminate cases and vowel-consonant-consonant-vowel (VCCV) for geminate cases. The consonants in the words are stops /b/, /d/, /g/, /p/, /t/, /k/, affricates /ts/, /dz/, /ʧ/, /ʤ/, fricatives /f/, /v/, /s/, /z/ (singleton only) and /ʃ/ (geminate only), nasals /m/, /n/ and /ɲ/ (geminate only), and liquids /l/, /r/ and /λ/ (geminate only). The database also includes recordings for glides (/j/, /w/). The vowels in the words are /a, i, u/; words are symmetric with respect to vowel.Six native adult speakers of Standard Italian, raised and living in Rome, Italy, three female and three male, uttered the speech materials in three different recording sessions; three repetitions for each word per speaker were therefore collected.The dataset also includes the durations of vowel and consonant segments for all cases where the consonant can be singleton vs. geminate (see [1] and [2]).

Phonological difficulties characterize individuals with dyslexia across languages. Currently debated is whether these difficulties arise from atypical neural sampling of (or entrainment to) auditory information in speech at slow rates (

The LaMIT database consists in recordings of 100 Italian sentences. The sentences in the database were designed so to include all phonemes of the Italian language, and also take into account the typical frequency of each phoneme in written Italian. Four native adult speakers of Standard Italian, raised and living in Rome, Italy, two female and two male, pronounced the sentences in two different recording sessions; two repetitions for each sentence per speaker were therefore collected, for a total of 800 recordings.The database was specifically created for application in the LaMIT project, that focuses on the application to the Italian language of the Lexical Access model proposed by Ken Stevens for American English. The model relies on the detection of specific acoustic discontinuities called landmarks and other acoustic cues to features that characterize each phoneme. Each recording was thus processed to generate a set of labeling files that identify both predicted landmarks and other cues, and actual landmarks/cues. The labeling files, compiled according to the labeling syntax used in the Praat speech processing software, are also made available as part of the LAMIT database.

In this study, we examined whether the facilitatory priming effect found when auditory primes and targets are related by a phoneme transposition (e.g., /ʀͻb/-/bͻʀ/: Dufour & Grainger, 2019, 2020) is also observed under cross-modal presentation. In two experiments using the same materials as in the previous studies, we found no evidence for a facilitatory priming effect when the targets were presented visually rather than auditorily. On the contrary, an inhibitory priming effect was found when both unrelated words (Experiment 1; e.g., /mas/-/bͻR/) and vowel overlap words (Experiment 2; e.g., /vͻl/-/bͻʀ/) were used as control conditions. In Experiment 2, this inhibitory effect was found to be equivalent in size whether the target words were of higher or lower frequency than the prime words (e.g. /ʀͻb/-/bͻʀ/ vs. /bͻʀ/-/ʀͻb/). We interpret this pattern of effects as reflecting the greater impact of word-level inhibition in cross-modal priming, and the parallel influence of prime-target relative frequency on bottom-up phoneme-to-word facilitation and word-level inhibition. Therefore, the facilitatory priming effect previously observed with auditory primes and targets would mainly reflect bottom-up activation of the target word representation during prime word processing.

Background: One key mechanism thought to underlie speech processing is the alignment of cortical brain rhythms to the acoustic input, a mechanism termed entrainment. Recent work showed that transcranial electrical stimulation (tES) in speech relevant frequencies or adapted to the speech envelope can in fact enhance speech processing. However, it is unclear whether an oscillatory tES is necessary, or if transients in the stimulation (e.g., peaks in the tES signal) at relevant times are sufficient. Objective: In this study we used a novel pulsed-tES-protocol and tested behaviorally if a transiently pulsed - instead of a persistently oscillating - tES signal, can improve speech processing. Methods: While subjects listened to spoken sentences embedded in noise, brief electric direct current pulses aligned to speech transients (syllable onsets) were applied to auditory cortex regions to modulate comprehension. Additionally, we modulated the temporal delay between tES-pulses and speech transients to test for periodic modulations of behavior, indicative of entrainment by tES. Results: Speech comprehension was improved when tES-pulses were applied with a delay of 100 ms in respect to the speech transients. Contradictory to previous reports we find no periodic modulation of behavior. However, we find indications that periodic modulations can be spurious results of sampling behavioral data too coarsely. Conclusions: Subject’s speech comprehension benefits from pulsed-tES, yet behavior is not modulated periodically. Thus, pulsed-tES can aid cortical entrainment to speech input, which is especially relevant in a noisy environment. Yet, pulsed-tES does not seem to entrain brain oscillations by itself.

A recent paper by Boswijk, Loerts & Hilton (Boswijk et al., 2020) in this journal discusses how technological advances allow us to explore the cognitive processing of so-called salient linguistic features, and how this could provide us with quantifiable measures of ‘salience’. The paper concludes that, although promising, the used measure of pupil dilation seems to be limited as a measure for linguistic salience, and therefore refers future research to other measures, specifically Event Related Potentials (ERPs). In this paper we therefore replicate the Boswijk et al. study using the ERP measure with the hypothesis that linguistic salience evokes distinct ERP components. We use the same materials that were used in the Boswijk et al. (2020) paper to observe changes in Dutch participants' pupil sizes when listening to stimuli containing salient and non-salient variants of linguistic variables.Using Generalized Additive Mixed Modelling (GAMM), we find distinct responses for five of six stimuli categories. We consider our findings in light of the literature on linguistic salience and discuss how our findings relate to the Boswijk et al. (2020) study. We find that ERPs provide a more fine-grained measure of theoretically salient stimuli.

Neural oscillations contribute to speech parsing via cortical tracking of hierarchical linguistic structures, including syllable rate. While the properties of neural entrainment have been largely probed with speech stimuli at either normal or artificially accelerated rates, the important case of natural fast speech has been largely overlooked. Using magnetoencephalography, we found that listening to naturally-produced speech was associated with cortico-acoustic coupling, both at normal (∼6 syllables/s) and fast (∼9 syllables/s) rates, with a corresponding shift in peak entrainment frequency. Interestingly, time-compressed sentences did not yield such coupling, despite being generated at the same rate as the natural fast sentences. Additionally, neural activity in right motor cortex exhibited stronger tuning to natural fast rather than to artificially accelerated speech, and showed evidence for stronger phase-coupling with left temporo-parietal and motor areas. These findings are highly relevant for our understanding of the role played by auditory and motor cortex oscillations in the perception of naturally produced speech.

In humans, social relationship with the speaker affects neural processing of speech, as exemplified by children’s auditory and reward responses to their mother's utterances. Family dogs show human analogue attachment behavior towards the owner, and neuroimaging revealed auditory cortex and reward center sensitivity to verbal praises in dog brains. Combining behavioral and non-invasive fMRI data, we investigated the effect of dogs’ social relationship with the speaker on speech processing. Dogs listened to praising and neutral speech from their owners and a control person. We found positive correlation between dogs’ behaviorally measured attachment scores towards their owners and neural activity increase for the owner’s voice in the caudate nucleus; and activity increase in the secondary auditory caudal ectosylvian gyrus and the caudate nucleus for the owner’s praise. Through identifying social relationship-dependent neural reward responses, our study reveals similarities in neural mechanisms modulated by infant-mother and dog-owner attachment.

Speech comprehension in natural soundscapes rests on the ability of the auditory system to extract speech information from a complex acoustic signal with overlapping contributions from many sound sources. Here we reveal the canonical processing of speech in natural soundscapes on multiple scales by using data-driven modeling approaches to characterize sounds to analyze ultra high field fMRI recorded while participants listened to the audio soundtrack of a movie. We show that at the functional level the neuronal processing of speech in natural soundscapes can be surprisingly low dimensional in the human cortex, highlighting the functional efficiency of the auditory system for a seemingly complex task. Particularly, we find that a model comprising three functional dimensions of auditory processing in the temporal lobes is shared across participants’ fMRI activity. We further demonstrate that the three functional dimensions are implemented in anatomically overlapping networks that process different aspects of speech in natural soundscapes. One is most sensitive to complex auditory features present in speech, another to complex auditory features and fast temporal modulations, that are not specific to speech, and one codes mainly sound level. These results were derived with few a-priori assumptions and provide a detailed and computationally reproducible account of the cortical activity in the temporal lobe elicited by the processing of speech in natural soundscapes.

Transcranial alternating current stimulation (tACS) can non-invasively modulate neuronal activity in the cerebral cortex, in particular at the frequency of the applied stimulation. Such modulation can matter for speech processing, since the latter involves the tracking of slow amplitude fluctuations in speech by cortical activity. tACS with a current signal that follows the envelope of a speech stimulus has indeed been found to influence the cortical tracking and to modulate the comprehension of the speech in background noise. However, how exactly tACS influences the speech-related cortical activity, and how it causes the observed effects on speech comprehension, remains poorly understood. A computational model for cortical speech processing in a biophysically plausible spiking neural network has recently been proposed. Here we extended the model to investigate the effects of different types of stimulation waveforms, similar to those previously applied in experimental studies, on the processing of speech in noise. We assessed in particular how well speech could be decoded from the neural network activity when paired with the exogenous stimulation. We found that, in the absence of current stimulation, the speech-in-noise decoding accuracy was comparable to the comprehension of speech in background noise of human listeners. We further found that current stimulation could alter the speech decoding accuracy by a few percent, comparable to the effects of tACS on speech-in-noise comprehension. Our simulations further allowed us to identify the parameters for the stimulation waveforms that yielded the largest enhancement of speech-in-noise encoding. Our model thereby provides insight into the potential neural mechanisms by which weak alternating current stimulation may influence speech comprehension and allows to screen a large range of stimulation waveforms for their effect on speech processing.

Poor neural speech discrimination has been connected to dyslexia, and may represent phonological processing deficits that are hypothesized to be the main cause for reading impairments. Thus far, neural speech discrimination impairments have rarely been investigated in adult dyslexics, and even less by examining sources of neuromagnetic responses. We compared neuromagnetic speech discrimination in dyslexic and typical readers with mismatch fields (MMF) and determined the associations between MMFs and reading-related skills. We expected weak and atypically lateralized MMFs in dyslexic readers, and positive associations between reading-related skills and MMF strength. MMFs were recorded to a repeating pseudoword /ta-ta/ with occasional changes in vowel identity, duration, or syllable frequency from 43 adults, 21 with confirmed dyslexia. Phonetic (vowel and duration) changes elicited left-lateralized MMFs in the auditory cortices. Contrary to our hypothesis, MMF source strengths or lateralization did not differ between groups. However, better verbal working memory was associated with stronger left-hemispheric MMFs to duration changes across groups, and better reading was associated with stronger right-hemispheric late MMFs across speech-sound changes in dyslexic readers. This suggests a link between neural speech processing and reading-related skills, in line with previous work. Furthermore, our findings suggest a right-hemispheric compensatory mechanism for language processing in dyslexia. The results obtained promote the use of MMFs in investigating reading-related brain processes.

Characterizing the neural dynamics underlying sensory processing is one of the central areas of investigation in systems and cognitive neuroscience. Neuroimaging techniques such as magnetoencephalography (MEG) and Electroencephalography (EEG) have provided significant insights into the neural processing of continuous stimuli, such as speech, thanks to their high temporal resolution. Existing work in the context of auditory processing suggests that certain features of speech, such as the acoustic envelope, can be used as reliable linear predictors of the neural response manifested in M/EEG. The corresponding linear filters are referred to as temporal response functions (TRFs). While the functional roles of specific components of the TRF are well-studied and linked to behavioral attributes such as attention, the cortical origins of the underlying neural processes are not as well understood. In this work, we address this issue by estimating a linear filter representation of cortical sources directly from neuroimaging data in the context of continuous speech processing. To this end, we introduce Neuro-Current Response Functions (NCRFs), a set of linear filters, spatially distributed throughout the cortex, that predict the cortical currents giving rise to the observed ongoing MEG (or EEG) data in response to continuous speech. NCRF estimation is cast within a Bayesian framework, which allows unification of the TRF and source estimation problems, and also facilitates the incorporation of prior information on the structural properties of the NCRFs. To generalize this analysis to M/EEG recordings which lack individual structural magnetic resonance (MR) scans, NCRFs are extended to free-orientation dipoles and a novel regularizing scheme is put forward to lessen reliance on fine-tuned coordinate co-registration. We present a fast estimation algorithm, which we refer to as the Champ-Lasso algorithm, by leveraging recent advances in optimization, and demonstrate its utility through application to simulated and experimentally recorded MEG data under auditory experiments. Our simulation studies reveal significant improvements over existing methods that typically operate in a two-stage fashion, in terms of spatial resolution, response function reconstruction, and recovering dipole orientations. The analysis of experimentally-recorded MEG data without MR scans corroborates existing findings, but also delineates the distinct cortical distribution of the underlying neural processes at high spatiotemporal resolution. In summary, we provide a principled modeling and estimation paradigm for MEG source analysis tailored to extracting the cortical origin of electrophysiological responses to continuous stimuli.

A novel scalable speech coding scheme based on Compressive Sensing (CS), which can operate at bit rates from 3.275 to 7.275 kbps is designed and implemented in this paper. The CS based speech coding offers the benefit of combined compression and encryption with inherent de-noising and bit rate scalability. The non-stationary nature of speech signal causes the recovery process from CS measurements very complex due to the variation in sparsifying bases. In this work, the complexity of the recovery process is reduced by assigning a suitable basis to each frame of the speech signal based on its statistical properties. As the quality of the reconstructed speech depends on the sensing matrix used at the transmitter, a variant of Binary Permuted Block Diagonal (BPBD) matrix is also proposed here which offers a better performance than that of the commonly used Gaussian random matrix. To improve the coding efficiency, formant filter coefficients are quantized using the conventional Vector Quantization (VQ) and an orthogonal mapping based VQ is developed for the quantization of CS measurements. The proposed coding scheme offers the listening quality for reconstructed speech similar to that of Adaptive Multi rate - Narrowband (AMR-NB) codec at 6.7 kbps and Enhanced Voice Services (EVS) at 7.2 kbps. A separate de-noising block is not required in the proposed coding scheme due to the inherent de-noising property of CS. Scalability in bit rate is achieved in the proposed method by varying the number of random measurements and the number of levels for orthogonal mapping in the VQ stage of measurements.

Eye gaze is a powerful ostensive cue in infant-caregiver interactions, with demonstrable effects on language acquisition. While the link between gaze following and later vocabulary is well-established, the effects of eye gaze on other aspects of language, such as speech processing, are less clear. In this EEG study, we examined the effects of the speaker's eye gaze on ten-month-old infants' neural tracking of naturalistic audiovisual speech, a marker for successful speech processing. Infants watched videos of a speaker telling stories, addressing the infant with direct or averted eye gaze. We assessed infants' speech-brain coherence at stress (1-1.75 Hz) and syllable (2.5-3.5 Hz) rates, tested for differences in attention by comparing looking times and EEG theta power in the two conditions, and investigated whether neural tracking predicts later vocabulary. Our results showed that infants' brains tracked the speech rhythm both at the stress and syllable rates, and that infants' neural tracking at the syllable rate predicted later vocabulary. However, speech-brain coherence did not significantly differ between direct and averted gaze conditions and infants did not show greater attention to direct gaze. Overall, our results suggest significant neural tracking at ten months, related to vocabulary development, but not modulated by speaker's gaze., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The ability to synchronize motor movements along with an auditory beat places stringent demands on the temporal processing and sensorimotor integration capabilities of the nervous system. Links between millisecond-level precision of auditory processing and the consistency of sensorimotor beat synchronization implicate fine auditory neural timing as a mechanism for forming stable internal representations of, and behavioral reactions to, sound. Here, for the first time, we demonstrate a systematic relationship between consistency of beat synchronization and trial-by-trial stability of subcortical speech processing in preschoolers (ages 3 and 4 years old). We conclude that beat synchronization might provide a useful window into millisecond-level neural precision for encoding sound in early childhood, when speech processing is especially important for language acquisition and development.

From birth, we perceive speech by hearing and seeing people talk. In adults cortical representations of visual speech are processed in the putative temporal visual speech area (TVSA), but it remains unknown how these representations develop. We measured infants' cortical responses to silent visual syllables and non-communicative mouth movements using functional Near-Infrared Spectroscopy. Our results indicate that cortical specialisation for visual speech may emerge during infancy. The putative TVSA was active to both visual syllables and gurning around 5 months of age, and more active to gurning than to visual syllables around 10 months of age. Multivariate pattern analysis classification of distinct cortical responses to visual speech and gurning was successful at 10, but not at 5 months of age. These findings imply that cortical representations of visual speech change between 5 and 10 months of age, showing that the putative TVSA is initially broadly tuned and becomes selective with age., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

For seventy years, auditory selective attention research has focused on studying the cognitive mechanisms of prioritizing the processing a 'main' task-relevant stimulus, in the presence of 'other' stimuli. However, a closer look at this body of literature reveals deep empirical inconsistencies and theoretical confusion regarding the extent to which this 'other' stimulus is processed. We argue that many key debates regarding attention arise, at least in part, from inappropriate terminological choices for experimental variables that may not accurately map onto the cognitive constructs they are meant to describe. Here we critically review the more common or disruptive terminological ambiguities, differentiate between methodology-based and theory-derived terms, and unpack the theoretical assumptions underlying different terminological choices. Particularly, we offer an in-depth analysis of the terms 'unattended' and 'distractor' and demonstrate how their use can lead to conflicting theoretical inferences. We also offer a framework for thinking about terminology in a more productive and precise way, in hope of fostering more productive debates and promoting more nuanced and accurate cognitive models of selective attention., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Alongside the currently used nasal swab testing, the COVID-19 pandemic situation would gain noticeable advantages from low-cost tests that are available at any-time, anywhere, at a large-scale, and with real time answers. A novel approach for COVID-19 assessment is adopted here, discriminating negative subjects versus positive or recovered subjects. The scope is to identify potential discriminating features, highlight mid and short-term effects of COVID on the voice and compare two custom algorithms. A pool of 310 subjects took part in the study; recordings were collected in a low-noise, controlled setting employing three different vocal tasks. Binary classifications followed, using two different custom algorithms. The first was based on the coupling of boosting and bagging, with an AdaBoost classifier using Random Forest learners. A feature selection process was employed for the training, identifying a subset of features acting as clinically relevant biomarkers. The other approach was centered on two custom CNN architectures applied to mel-Spectrograms, with a custom knowledge-based data augmentation. Performances, evaluated on an independent test set, were comparable: Adaboost and CNN differentiated COVID-19 positive from negative with accuracies of 100% and 95% respectively, and recovered from negative individuals with accuracies of 86.1% and 75% respectively. This study highlights the possibility to identify COVID-19 positive subjects, foreseeing a tool for on-site screening, while also considering recovered subjects and the effects of COVID-19 on the voice. The two proposed novel architectures allow for the identification of biomarkers and demonstrate the ongoing relevance of traditional ML versus deep learning in speech analysis., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Authors Giovanni Costantini, Giovanni Saggio, and Antonio Pisani are advisory members of VoiceWise S.r.l., spin-off company of University of Rome Tor Vergata (Rome, Italy) developing voice analysis solutions for diagnostic purposes; Valerio Cesarini cooperates with VoiceWise and is employed by CloudWise S.r.l., a company developing cloud data storage and software solutions., (© 2022 Elsevier B.V. All rights reserved.)

Objective: In binaurally deaf subjects, speech processing particularly benefits from a cochlear implant (CI) in the right ear, which is contralateral to the commonly left speech-dominant hemisphere. However, it is unclear whether such effects of implantation side also occur in speech processing in patients with single-sided deafness (SSD)., Methods: Lateralization of N1 responses was analyzed with a high-density electroencephalogram (EEG) in fourteen adults with postlingually acquired left or right SSD who received a CI in adulthood. During recording, patients performed a speech and a pure-tone discrimination task. Lateralization of N1 responses was assessed by side-specific global field power (GFP) and compared (a) between normal hearing and CI-implanted ears within subjects and (b) between implantation sides across subjects., Results: N1 responses were stronger in the contralateral than in the ipsilateral hemisphere during stimulation of the normal hearing ear (except for left speech stimulation), and was bilateral symmetric with CI stimulation on either side. A significant correlation between speech discrimination performance and left lateralization was found across subjects for the left CI ear., Conclusions: CI stimulation altered auditory processing across hemispheres. Speech discrimination in left CI-implanted SSD patients improved with left lateralization of the N1 response., Significance: Side-specific rehabilitation in SSD patients might improve speech processing across hemispheres., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. B.S. received travel expenses from Cochlear Deutschland GmbH & Co. KG outside of the submitted work., (Copyright © 2022 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Both visual articulatory gestures and orthography provide information on the phonological content of speech. This EEG study investigated the integration between speech and these two visual inputs. A comparison of skilled readers' brain responses elicited by a spoken word presented alone versus synchronously with a static image of a viseme or a grapheme of the spoken word's onset showed that while neither visual input induced audiovisual integration on N1 acoustic component, both led to a supra-additive integration on P2, with a stronger integration between speech and graphemes on left-anterior electrodes. This pattern persisted in P350 time-window and generalized to all electrodes. The finding suggests a strong impact of spelling knowledge on phonetic processing and lexical access. It also indirectly indicates that the dynamic and predictive value present in natural lip movements but not in static visemes is particularly critical to the contribution of visual articulatory gestures to speech processing., (Copyright © 2021 Elsevier Inc. All rights reserved.)