Speech Task Research Articles

Task-Dependent Modulation of Auditory Feedback Control of Vocal Intensity

Auditory feedback control of fundamental frequency (fo) is modulated in a task-dependent manner. When voice pitch auditory feedback perturbations are applied in sentence versus sustained-vowel production, larger and faster vocal fo responses are measured in sentence production. This task-dependency reflects the scaling of auditory targets for pitch for the precision required in each speech task. When the range for the pitch auditory target is scaled down for precision (as in the sentence-production task), a greater degree of mismatch is detected from the feedback perturbation and a larger vocal response is measured. The purpose of this study was to determine whether auditory feedback control of vocal intensity is also modulated in a task-dependent manner similar to the control of vocal pitch. Twenty-five English speakers produced repetitions of a sentence and a sustained vowel while hearing their voice auditory feedback briefly perturbed in loudness (+/- 3 or 6 dB SPL, 200 ms duration). The resulting vocal intensity responses were measured, and response magnitudes were robustly larger in the sentence (mean: 1.96 dB) than vowel production (mean: 0.89 dB). Additionally, response magnitudes increased as a function of perturbation magnitude only in sentence production for downward perturbations but decreased in magnitude by perturbation magnitude for upward perturbations. Peak response latencies were robustly shorter in sentence (mean: 184.94 ms) than in vowel production (mean: 214.92 ms). Overall, these results support the hypothesis that auditory feedback control of pitch and loudness are modulated by task and that both pitch and loudness auditory targets are scaled for the precision required for the speaking task.

RemixIT: Continual Self-Training of Speech Enhancement Models via Bootstrapped Remixing

We present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RemixIT</i> , a simple yet effective self-supervised method for training speech enhancement without the need of a single isolated in-domain speech nor a noise waveform. Our approach overcomes limitations of previous methods which make them dependent on clean in-domain target signals and thus, sensitive to any domain mismatch between train and test samples. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RemixIT</i> is based on a continuous self-training scheme in which a pre-trained teacher model on out-of-domain data infers estimated pseudo-target signals for in-domain mixtures. Then, by permuting the estimated clean and noise signals and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">remixing</i> them together, we generate a new set of bootstrapped mixtures and corresponding pseudo-targets which are used to train the student network. Vice-versa, the teacher periodically refines its estimates using the updated parameters of the latest student models. Experimental results on multiple speech enhancement datasets and tasks not only show the superiority of our method over prior approaches but also showcase that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RemixIT</i> can be combined with any separation model as well as be applied towards any semi-supervised and unsupervised domain adaptation task. Our analysis, paired with empirical evidence, sheds light on the inside functioning of our self-training scheme wherein the student model keeps obtaining better performance while observing severely degraded pseudo-targets.

Self-Supervised Learning With Segmental Masking for Speech Representation

Self-supervised learning has achieved remarkable success for learning speech representations from unlabeled data. The masking strategy plays an important role in the self-supervised learning algorithm. Most of the masking techniques operate at a frame level. In linguistics, phone is the smallest unit of sound. Hence, we believe that a masking technique that operates at a phoneme level will effectively encode the phonotactic and prosodic constraints of a spoken language, thus eventually benefits the downstream speech recognition tasks. In this work, we explore a novel segmental masking strategy. Specifically, we mask phonetically motivated speech segments according to the phonetic segmentation in an utterance. By doing so, we implicitly incorporate the properties of a spoken language, such as phonotactic constraints and duration of phonetic segments, into the pre-training. Through extensive experiments, we confirm that the segmental masking strategy consistently outperforms the frame-based masking counterpart. We also further investigate the effect of segmental masking unit size, i.e. phoneme, phoneme span, and lexical word. This work presents an important finding about masking strategy in speech representation learning.

Immediate Effects of Combining Kinesio Tape with Voice Therapy in Patients with Muscle Tension Dysphonia

The present study investigated the immediate effect of adding Kinesio taping along with voice therapy for the treatment of muscle tension dysphonia patients. Twenty patients with primary muscle tension dysphonia (MTD) (12 males and 8 females) with a mean age of 36.95 ± 9.58 years participated in the study. Participants were assigned to two groups: one group (6 males and 4 females) received only traditional voice therapy (VT) and the other group (6 males and 4 females) received Kinesio taping (KT) and voice therapy (VT). The VT group received laryngeal manual therapy (LMT) (for 15 minutes) and voice therapy techniques including humming, chewing, and yawn-sigh (for 15 minutes). The VT+KT group received both KT and the same VT as the first group. KT was applied to the sternocleidomastoid, infralaryngeal, and supralaryngeal muscles of the neck. Auditory-perceptual assessments using CAPE-V, acoustic voice analysis, and assessments of vocal tract discomfort and pain were used to evaluate the effects of a single treatment session. The Wilcoxon and Mann-Whitney U tests were used for data analysis. The results of within-group comparison of the auditory-perceptual assessment (overall severity, roughness, breathiness, and strain) in both sustained vowels and connected speech tasks showed a significant reduction in all mentioned items in both groups (P < 0.05). Acoustic voice analysis showed significant improvement of HNR in the KT+VT group for both sustained vowels and connected speech tasks, and significant improvement of jitter in the VT group for sustained vowels (P < 0.05). Regarding vocal tract discomfort, the symptom of tightness in the KT+VT group, irritability and pain in the VT group, and the overall score of vocal tract discomfort in both groups, significantly decreased (P < 0.05). A significant decrease in pain severity in the front of the neck, throat, and larynx was reported by MTD patients in both groups (P < 0.05). Between-group comparisons indicated a significant difference only in the pain item of the VTD scale (P < 0.05) with greater pain decrease for the VT group. Comparison of the mean of differences showed that the VT group reduced irritability more than the KT+VT group (P < 0.05). The present study showed that voice therapy with and without Kinesio taping can improve patients' voice quality (auditory-perceptual and acoustic voice analysis) and reduce vocal tract discomfort and pain in MTD patients after one therapy session. Moreover, MTD patients treated with KT+VT did not experience more significant improvements compared to those treated with VT alone. More studies in this area are recommended to better determine the effects of KT in MTD patients especially for long term effects of KT.

Autoregressive Predictive Coding: A Comprehensive Study

We review autoregressive predictive coding (APC), an approach to learn speech representation by predicting a future frame given the past frames. We present three different views of interpreting APC, and provide a historical account to the approach. To study the speech representation learned by APC, we use common speech tasks, such as automatic speech recognition and speaker verification, to demonstrate the utility of the learned representation. In addition, we design a suite of fine-grained tasks, including frame classification, segment classification, fundamental frequency tracking, and duration prediction, to probe the phonetic and prosodic content of the representation. The three views of the APC objective welcome various generalizations and algorithms to learn speech representations. Probing on the suite of fine-grained tasks suggests that APC makes a wide range of high-level speech information accessible in its learned representation.

Developing a voice monitoring smartphone app: Acoustic acquisition and processing considerations

With the advent of smartphone technology, there has been an increase in at-home health monitoring. Yet, there are few applications (apps) available to track voice acoustics for those with voice disorders. Therefore, we completed two investigations into the acquisition and processing of the acoustic signal to help develop a voice monitoring app. Study 1: We investigated how microphone distance and phone tilt impact the accuracy of acoustic measures of voice. A total of 58 participants with (n = 47) and without (n = 11) voice disorders completed speech tasks of sustained vowels and the rainbow passage. Concurrent recordings were collected using the participant’s phone, as well as a stationary headset microphone for comparison. We determined that the voice measures of fundamental frequency (Hz), voicing duration (seconds), and cepstral peak prominence (dB) were impervious to phone distance and tilt. Study 2: Focusing on the three acoustic measures from study 1, we investigated the correspondence between acoustic measures attained with clinically available software (e.g., Praat) and those from our own lab-developed algorithms specialized for on-app processing. Preliminary results show strong relationships (r &amp;gt; .90) between the different processing techniques. Further work is needed to understand how participant-specific factors (age, dysphonia severity) may improve algorithm accuracy.

Role of superior temporal gyrus and planum temporale in talker segregation

Recent studies suggest the brain tracks both attended and unattended speech streams. Here, we describe the cortical mechanisms that support active talker segregation by vocal gender. Thirty-three participants with normal or near-normal hearing performed a competing speech task during fMRI scanning. The target (competing) talker was female (male). Spectrotemporal modulation filtering was applied to stochastically modulate female and male vocal pitch across trials. Using the modulation-filter patterns as predictors, spectrotemporal receptive fields (STRFs) were obtained at each voxel using coordinate descent. STRF weights associated with female- (∼6 cyc/kHz) and male-talker (∼12 cyc/kHz) pitch were analyzed across subjects to identify pitch-sensitive voxels (logical OR, corrected p &amp;lt; 0.01), which were then characterized by preference for female vs. male. Anterior regions in Heschl’s gyrus and the superior temporal gyrus (STG) responded best to the female talker, while posterior regions in STG and planum temporale (PT) responded best to the male talker. In a control task where the talkers did not compete, the same pattern was observed but the posterior network shifted from STG to PT and responded to the acoustic boundary between talkers (∼9 cyc/kHz), suggesting that acoustically coded pitch in PT becomes voice-coded in STG during active segregation.

Music and Speech Perception in Prelingually Deafened Young Listeners With Cochlear Implants: A Preliminary Study Using Sung Speech.

In the context of music and speech perception, this study aimed to assess the effect of variation in one of two auditory attributes-pitch contour and timbre-on the perception of the other in prelingually deafened young cochlear implant (CI) users, and the relationship between pitch contour perception and two cognitive functions of interest. Nine prelingually deafened CI users, aged 8.75-22.17 years, completed a melodic contour identification (MCI) task using stimuli of piano notes or sung speech with a fixed timbre (same word for each note) or a mixed timbre (different words for each note), a speech perception task identifying matrix-styled sentences naturally intonated or sung with a fixed pitch (same pitch for each word) or a mixed pitch (different pitches for each word), a forward digit span test indexing auditory short-term memory (STM), and the matrices section of the Kaufman Brief Intelligence Test-Second Edition indexing nonverbal IQ. MCI was significantly poorer for the mixed timbre condition. Speech perception was significantly poorer for the fixed and mixed pitch conditions than for the naturally intonated condition. Auditory STM positively correlated with MCI at 2- and 3-semitone note spacings. Relative to their normal-hearing peers from a related study using the same stimuli and tasks, the CI participants showed comparable MCI at 2- or 3-semitone note spacing, and a comparable level of significant decrement in speech perception across three pitch contour conditions. Findings suggest that prelingually deafened CI users show similar trends of normal-hearing peers for the effect of variation in pitch contour or timbre on the perception of the other, and that cognitive functions may underlie these outcomes to some extent, at least for the perception of pitch contour. https://doi.org/10.23641/asha.21217937.

Correlation between Ratios of Word-finding Behavior and CIU in Patients with Mild Cognitive Impairment and Dementia of Alzheimer’s Type

Objectives: Anomia is the primary language symptom in patients with mild cognitive impairment (MCI) and dementia of Alzheimer’s type (DAT). The purpose of this study was to examine the correlation between the ratios of word-finding behavior and Correct information Unit (CIU) through spontaneous speech task in patients with MCI and DAT. Methods: The participants of this study were 31 healthy elderly, 29 patients with MCI, and 27 patients with mild DAT. The picture description tasks were used, and word-finding behaviors and CIU ratio analysis were used. Results: First, it was found that there were significant differences according to groups in the ratio of empty words, repetitions, insertions, and global index. Second, there was no significant correlation between the ratio of word-finding behavior and the CIU ratio in the healthy elderly, but there were significant correlations between the ratios of the word-finding behavior and the CIU ratio in patients with MCI and DAT. Finally, according to the regression analysis results, it was found that the ratio of the global index significantly predicted the CIU ratio in the MCI and DAT groups. Conclusion: From the results of this study, it can be seen that the ratios of word-finding behavior through spontaneous speech tasks in patients with MCI and DAT is related to information delivery ability.

LIP TO SPEECH AND TEXT SYNTHESIS

Humans involuntarily tend to infer parts of the conversation from lip movements when the speech is absent or corrupted by external noise.In this work, we explore the task of lip to speech synthesis, i.e., learning to generate natural speech given only the lip movements of a speaker. Acknowledging the importance of contextual and speaker specific cues for accurate lip-reading, we take a different path from existing works.We focus on learning accurate lip sequences to speech mappings for individual speakers in unconstrained, large vocabulary settings. We collect and release a large-scale benchmark dataset, the first of its kind, specifically to train and evaluate the single speaker lip to speech task in natural settings.We propose a novel approach with key design choices to achieve accurate, natural lip to speech synthesis in such unconstrained scenarios for the first time. Extensive evaluation using quantitative, qualitative metrics and human evaluation shows that our method is four times more intelligible than previous works in this space.

TDCS modulates speech perception and production in second language learners

Accurate identification and pronunciation of nonnative speech sounds can be particularly challenging for adult language learners. The current study tested the effects of a brief musical training combined with transcranial direct current stimulation (tDCS) on speech perception and production in a second language (L2). The sample comprised 36 native Hebrew speakers, aged 18–38, who studied English as L2 in a formal setting and had little musical training. Training encompassed musical perception tasks with feedback (i.e., timbre, duration, and tonal memory) and concurrent tDCS applied over the left posterior auditory-related cortex (including posterior superior temporal gyrus and planum temporale). Participants were randomly assigned to anodal or sham stimulation. Musical perception, L2 speech perception (measured by a categorical AXB discrimination task) and speech production (measured by a speech imitation task) were tested before and after training. There were no tDCS-dependent effects on musical perception post-training. However, only participants who received active stimulation showed increased accuracy of L2 phoneme discrimination and greater change in the acoustic properties of L2 speech sound production (i.e., second formant frequency in vowels and center of gravity in consonants). The results of this study suggest neuromodulation can facilitate the processing of nonnative speech sounds in adult learners.

Psychometric properties of the state Probability and Consequences Questionnaire for social anxiety disorder

Cognitive models of social anxiety propose that overestimation of the probability and cost of negative evaluation plays a central role in maintaining the disorder. However, there are currently no self-report state-based measures of probability and cost appraisals. The current paper examines the psychometric properties of the Probability and Consequences Questionnaire for social anxiety (PCQ-SA), which measures probability and consequence appraisals both in anticipation of, and in response to, an impromptu speech task. A total of 532 participants were recruited for the present study, consisting of 409 participants with a principal diagnosis of Social Anxiety Disorder (SAD), and 123 non-clinical controls. Results of exploratory and confirmatory factor analyses supported a two-factor solution for the PCQ-SA. The PCQ-SA demonstrated excellent internal consistency, excellent test-retest reliability, good convergent validity at both time points (i.e., pre and post speech task), and sensitivity to treatment. Finally, using Receiver Operating Characteristic Curve Analysis, clinical cut-off scores were calculated for probability and consequences at both time points, with the PCQ-SA scales showing good sensitivity, specificity, and positive and negative predictive values. Overall, the results provide evidence that the PCQ-SA possesses excellent psychometric properties. The PCQ-SA is suitable for use in clinical and research settings to assess key cognitive maintaining factors for SAD.

Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis.

BackgroundSpeech data for medical research can be collected noninvasively and in large volumes. Speech analysis has shown promise in diagnosing neurodegenerative disease. To effectively leverage speech data, transcription is important, as there is valuable information contained in lexical content. Manual transcription, while highly accurate, limits the potential scalability and cost savings associated with language-based screening.ObjectiveTo better understand the use of automatic transcription for classification of neurodegenerative disease, namely, Alzheimer disease (AD), mild cognitive impairment (MCI), or subjective memory complaints (SMC) versus healthy controls, we compared automatically generated transcripts against transcripts that went through manual correction.MethodsWe recruited individuals from a memory clinic (“patients”) with a diagnosis of mild-to-moderate AD, (n=44, 30%), MCI (n=20, 13%), SMC (n=8, 5%), as well as healthy controls (n=77, 52%) living in the community. Participants were asked to describe a standardized picture, read a paragraph, and recall a pleasant life experience. We compared transcripts generated using Google speech-to-text software to manually verified transcripts by examining transcription confidence scores, transcription error rates, and machine learning classification accuracy. For the classification tasks, logistic regression, Gaussian naive Bayes, and random forests were used.ResultsThe transcription software showed higher confidence scores (P<.001) and lower error rates (P>.05) for speech from healthy controls compared with patients. Classification models using human-verified transcripts significantly (P<.001) outperformed automatically generated transcript models for both spontaneous speech tasks. This comparison showed no difference in the reading task. Manually adding pauses to transcripts had no impact on classification performance. However, manually correcting both spontaneous speech tasks led to significantly higher performances in the machine learning models.ConclusionsWe found that automatically transcribed speech data could be used to distinguish patients with a diagnosis of AD, MCI, or SMC from controls. We recommend a human verification step to improve the performance of automatic transcripts, especially for spontaneous tasks. Moreover, human verification can focus on correcting errors and adding punctuation to transcripts. However, manual addition of pauses is not needed, which can simplify the human verification step to more efficiently process large volumes of speech data.

Motion energy analysis during speech tasks in medication-naïve individuals with at-risk mental states for psychosis

Movement abnormalities are commonly observed in schizophrenia and at-risk mental states (ARMS) for psychosis. They are usually detected with clinical interviews, such that automated analysis would enhance assessment. Our aim was to use motion energy analysis (MEA) to assess movement during free-speech videos in ARMS and control individuals, and to investigate associations between movement metrics and negative and positive symptoms. Thirty-two medication-naïve ARMS and forty-six healthy control individuals were filmed during speech tasks. Footages were analyzed using MEA software, which assesses movement by differences in pixels frame-by-frame. Two regions of interest were defined—head and torso—and mean amplitude, frequency, and coefficient of variability of movements for them were obtained. These metrics were correlated with the Structured Interview for Prodromal Syndromes (SIPS) symptoms, and with the risk of conversion to psychosis—inferred with the SIPS risk calculator. ARMS individuals had significantly lower mean amplitude of head movement and higher coefficients of movement variability for both head and torso, compared to controls. Higher coefficient of variability was related to higher risk of conversion. Negative correlations were seen between frequency of movement and most SIPS negative symptoms. All positive symptoms were correlated with at least one movement variable. Movement abnormalities could be automatically detected in medication-naïve ARMS subjects by means of a motion energy analysis software. Significant associations of movement metrics with symptoms were found, supporting the importance of movement analysis in ARMS. This could be a potentially important tool for early diagnosis, intervention, and outcome prediction.

Brainstem speech encoding is dynamically shaped online by fluctuations in cortical [formula omitted] state

Experimental evidence in animals demonstrates cortical neurons innervate subcortex bilaterally to tune brainstem auditory coding. Yet, the role of the descending (corticofugal) auditory system in modulating earlier sound processing in humans during speech perception remains unclear. Here, we measured EEG activity as listeners performed speech identification tasks in different noise backgrounds designed to tax perceptual and attentional processing. We hypothesized brainstem speech coding might be tied to attention and arousal states (indexed by cortical α power) that actively modulate the interplay of brainstem-cortical signal processing. When speech-evoked brainstem frequency-following responses (FFRs) were categorized according to cortical α states, we found low α FFRs in noise were weaker, correlated positively with behavioral response times, and were more ”decodable” via neural classifiers. Our data provide new evidence for online corticofugal interplay in humans and establish that brainstem sensory representations are continuously yoked to (i.e., modulated by) the ebb and flow of cortical states to dynamically update perceptual processing.

P01.12.B Analysis of semi-spontaneous speech before, during and after awake craniotomy: a case study

Abstract Background The standard treatment for patients with eloquent gliomas is awake craniotomy (AC) with direct electrical stimulation, which results in a larger extent of resection while maintaining language function. Intraoperative language monitoring includes different standardized tasks and spontaneous speech elicitation. Despite careful monitoring, it was found that spontaneous speech deteriorated long-term after surgery. However, intraoperative spontaneous speech has not been investigated before. Detailed analyses may reveal possible predictors for language outcome. For the first time, we present a case study in which we investigate and quantify semi-spontaneous speech before, during and after AC. Material and Methods A left-handed 50-year old male with a glioblastoma (WHO grade 4) in the left parietal lobe underwent AC. Semi-spontaneous speech was collected (audio/video recording) using the Sabadel story retelling task at: 1 day before (T1), during (T2), 2 days (T3) and 2 months (T4) after surgery. Recordings were manually transcribed and language errors were quantified. A preliminary acoustic analysis with simple automatic peak detection was performed. Comparisons between test moments were made. Results Manual transcription showed 1) notable changes in the number of paraphasias (T1: 1% - T2: 1% - T3: 9% - T4: 5%), interjections (T1: 9% - T2: 9% - T3: 15% - T4: 10%), minimal utterances (T1: 4% - T2: 4% - T3: 6% - T4: 1%), false starts (T1: 3% - T2: 5% - T3: 6% - T4: 8%), self-corrections (T1: 3% - T2: 2% - T3: 4% - T4: 7%) and 2) small changes in repetitions (T1: 1% - T2: 0% - T3: 2% - T4: 3%), hesitations (T1: 1% - T2: 0% - T3: 2% - T4: 0%), incomplete sentences (T1: 1% - T2: 0% - T3: 0% - T4: 1%), grammatical errors (T1: 2% - T2: 1% - T3: 2% - T4: 2%). The total number of words (T1: 273 - T2: 283 - T3: 249 - T4: 287) and utterances (T1: 39 - T2: 41 - T3: 36 - T4: 34) varied slightly. Acoustic analysis showed a slight increase in word length during and directly after surgery but it recovered to preoperative level on the long-term (T1: .66 s - T2: .75 s - T3: .87 s - T4: .69 s). Conclusion The semi-spontaneous speech task in this case study was sensitive to capture changes in perioperative language status. Paraphasias, interjections, minimal utterances, hesitations and word length increased directly after surgery followed by a decrease 2 months later. This is a frequently reported pattern of transient language deficits. However, other errors (false starts, repetitions, self-corrections, incomplete sentences) increased at 2 months after surgery, indicating longer term language deficits. Future exploration of both the acoustic analysis, which shows potential for real-time feedback, and the manual transcriptions, could possibly lead to a better understanding of intra- and postoperative language performance as a prognostic factor for long-term language outcome, with possible implications for language therapy.

Measuring Communicative Congruence and Communicative Dysphoria in a Sample of Individuals Without Voice Disorders.

This study examines communicative congruence and communicative dysphoria in adults who deny having a voice disorder. Communicative congruence is the degree to which a person's communication is consistent with their sense of self/identity. Communicative dysphoria is the psychological entropy resulting from communicative incongruence. We propose that these experiences may influence patients' psychosocial well-being and are thus relevant to the field of speech-language pathology. We hypothesized that both constructs would be normally distributed with an inverse relationship. We also hypothesized that communicative congruence would predict scores on the Center for Epidemiological Studies-Depression (CES-D) scale, subscales of the Big Five Aspect Scales (BFAS; a personality measure), and achieve convergent validity with the Vocal Congruence Scale (VCS). Participants (adults 18-70 years) completed the BFAS, CES-D, VCS, and the Voice Handicap Index-10 (VHI-10) before recording a series of speech tasks. Participants' recordings were played back while they responded to questions probing their communicative congruence and communicative dysphoria. The 196 participants were predominantly female (67.3%) and cisgender (96.4%). Communicative congruence was negatively skewed, and communicative dysphoria was normally distributed. Both variables significantly related to each other: More incongruence was associated with more dysphoria. Communicative congruence was inversely related to CES-D scores. The personality metatrait Plasticity related to communicative congruence, as did the domain of Extraversion and the aspects Withdrawal, Enthusiasm, and Assertiveness. Communicative congruence achieved high convergent validity with the VCS. Counter to our hypothesis, participants reported more congruence than incongruence, but all other hypotheses were supported. Participants who reported incongruence were more likely to report symptoms of depression. These findings suggest that even in a predominantly cisgender cohort, some individuals' mental well-being might relate to how well their communication aligns with their identity. This work may inform future investigations into these constructs and their effects on voice therapy outcomes. https://doi.org/10.23641/asha.20739967.

Task Planning and Oral L2 Production: A Research Synthesis and Meta-analysis

AbstractIncreased second language acquisition (SLA) research interest in the effect of planning on subsequent L2 oral production has typically examined the effect of planning on the syntactic complexity, accuracy, lexical complexity, and/or fluency (CALF) of L2 production. However, the results of research in this domain are inconclusive. This study, a research synthesis and meta-analysis of SLA research on the effects of planning on the CALF of L2 oral production, attempts to facilitate a direct comparison of such research, first by examining the role of planning in theoretical models of (i) speech production, (ii) task complexity, and (iii) task readiness; second by summarizing the features of SLA research on planning; and finally by comparing the results of quantitative research on the effect of planning on subsequent L2 production. The results of the research synthesis portion of the study suggest a number of consistencies in SLA research on planning to date, whereas the results of the meta-analysis portion of the study suggest clear effects of planning on L2 oral production and have clear pedagogical implications for L2 instruction.

EEG coherence as a marker of functional connectivity disruption in Alzheimer's disease

Progressive deterioration of connectivity between neurons is a neurophysiological hallmark of brain ageing and has been linked to the severity of dementia. We explored the possibility of utilizing electroencephalographic evidence of functional connectivity disruption as a potential marker of Alzheimer's disease. This study examined group differences in EEG coherence within global cortical networks at rest and during executive challenges among patients with Alzheimer's dementia, individuals with mild cognitive impairment, and healthy controls. Four promising EEG coherence markers were identified as (i) F3-F4 Beta in visual-spatial orientation task (p = 0.019), (ii) P7-P8 Beta in writing task (p = 0.001), (iii) T7-T8 Gamma in speech understanding task (p = 0.008) and (iv) O1-O2 Alpha in space orientation task (p = 0.020). More research is needed to identify the sensitivity and specificity of the markers.

A-8 Neurocognitive Inhibition Predicts Cortisol Reactivity to a Stressful Speech Task

Abstract Objective: Increased stress and cortisol are important risk factors for cardiovascular diseases, including cerebrovascular disease. The present study used an experimental speech task to determine the relationship between inhibitory control and cortisol response to social stress. We hypothesized that poorer inhibitory control would predict larger cortisol response to the stressor. Method: Participants were 42 women with overweight/obesity recruited for larger project examining the impacts of weight stigma on inflammation. The computerized Stroop Color-Word and Go/No-Go assessed baseline inhibitory control and other neurocognitive factors. Higher scores indicate better performance. After a baseline blood sample, participants were randomized and asked to give a speech (1 = stigma, 0 = neutral). Subsequent blood draws were taken at 30-, 60-, and 90-minutes post-speech. Area under the curve was calculated to represent total cortisol increase. Results: Analyses, controlling for speech condition and BMI, revealed that cortisol reactivity to the speech task was predicted by both Stroop Color-Word (β = −0.42, p = 0.007) and Interference (β = −0.35, p = 0.022) scores, as well as Go/No-Go Hits (β = −0.33, p = 0.04) and Omissions (β = −0.34, p = 0.03), but not Commissions (β = −0.038; p = 0.81). Conclusions: The pattern of results suggests that individuals with lower inhibitory control experienced a greater cortisol output after the stressor. In this context, individuals who were better able to ignore irrelevant social aspects of the speech experienced a smaller cortisol reaction than the individuals who could not ignore them. To reduce risk for cerebrovascular disease, clinical interventions should focus on the practice of ignoring irrelevant stressors to promote more adaptive biological responses to stress.