Toward a cumulative science of vocal markers of autism: A cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children

Evidence for Infant-directed Speech Preference Is Consistent Across Large-scale, Multi-site Replication and Meta-analysis

There is substantial evidence that infants prefer infant-directed speech (IDS) to adult-directed speech (ADS). The strongest evidence for this claim has come from two large-scale investigations: i) a community-augmented meta-analysis of published behavioral studies and ii) a large-scale multi-lab replication study. In this paper, we aim to improve our understanding of the IDS preference and its boundary conditions by combining and comparing these two data sources across key population and design characteristics of the underlying studies. Our analyses reveal that both the meta-analysis and multi-lab replication show moderate effect sizes (d ≈ 0.35 for each estimate) and that both of these effects persist when relevant study-level moderators are added to the models (i.e., experimental methods, infant ages, and native languages). However, while the overall effect size estimates were similar, the two sources diverged in the effects of key moderators: both infant age and experimental method predicted IDS preference in the multi-lab replication study, but showed no effect in the meta-analysis. These results demonstrate that the IDS preference generalizes across a variety of experimental conditions and sampling characteristics, while simultaneously identifying key differences in the empirical picture offered by each source individually and pinpointing areas where substantial uncertainty remains about the influence of theoretically central moderators on IDS preference. Overall, our results show how meta-analyses and multi-lab replications can be used in tandem to understand the robustness and generalizability of developmental phenomena.

Repeat After Me? Both Children With and Without Autism Commonly Align Their Language With That of Their Caregivers

Linguistic repetitions in children are conceptualized as negative in children with autism - echolalia, without communicative purpose - and positive in typically developing (TD) children - linguistic alignment involved in shared engagement, common ground and language acquisition. To investigate this apparent contradiction we analyzed spontaneous speech in 67 parent-child dyads from a longitudinal corpus (30 minutes of play activities at 6 visits over 2 years). We included 32 children with autism and 35 linguistically matched TD children (mean age at recruitment 32.76 and 20.27 months). We found a small number of exact repetitions in both groups (roughly 1% of utterances across visits), which increased over time in children with autism and decreased in the TD group. Partial repetitions were much more frequent: children reused caregivers' words at high rates regardless of diagnostic group (24% of utterances at first visit), and this increased in frequency (but not level) over time, faster for TD children (at final visit: 33% for autism, 40% for TD). The same happened for partial repetition of syntax and semantic alignment. However, chance alignment (as measured by surrogate pairs) also increased and findings for developmental changes were reliable only for syntactic and semantic alignment. Children with richer linguistic abilities also displayed a higher tendency to partially re-use their caregivers' language (alignment rates and semantic alignment). This highlights that all children commonly re-used the words, syntax, and topics of their caregivers, albeit with some quantitative differences, and that most repetition was at least potentially productive, with repeated language being re-contextualized and integrated with non-repeated language. The salience of echolalia in ASD might be partially explained by slight differences in frequency, amplified by lower semantic alignment, persistence over time, and expectations of echolalia. More in-depth qualitative and quantitative analyses of how repetitions are used and received in context are needed.

Infant-directed speech does not always involve exaggerated vowel distinctions: Evidence from Danish

This study compared the acoustic properties of 26 (100% female, 100% monolingual) Danish caregivers' spontaneous speech addressed to their 11- to 24-month-old infants (infant-directed speech, IDS) and an adult experimenter (adult-directed speech, ADS). The data were collected between 2016 and 2018 in Aarhus, Denmark. Prosodic properties of Danish IDS conformed to cross-linguistic patterns, with a higher pitch, greater pitch variability, and slower articulation rate than ADS. However, an acoustic analysis of vocalic properties revealed that Danish IDS had a reduced or similar vowel space, higher within-vowel variability, raised formants, and lower degree of vowel discriminability compared to ADS. None of the measures, except articulation rate, showed age-related differences. These results push for future research to conduct theory-driven comparisons across languages with distinct phonological systems.

The role of interpersonal synchrony in forming impressions of autistic and non-autistic adults

When people meet, they almost instantaneously form an impression of each other. First impressions of character traits and rapport are less favourable when people with autism spectrum condition (ASC) are judged compared to non-autistic people. Little is known about the behavioural differences that drive these altered impressions. In the present study, we investigated the influence of interpersonal synchrony on impression formation of autistic and non-autistic people. Specifically, we used lagged cross-correlations to assess how much each interactant's motion energy, a measure which can be determined from video recordings, influenced the other interactant's motion energy. In short, silent clips of dyadic conversations, we asked non-autistic participants to rate their impression of one of the two interactants, which was solely based on the outlines of both interactants. We expected that the amount of leading of the target interactant, their diagnostic status as well as the interaction of these factors would influence impression formation. We found that while the amount of leading had a positive effect on the impressions of non-autistic interactants, this was not true for interactants with ASC. This suggests that interpersonal synchrony of motion energy is one driver of less favourable impressions of autistic compared to non-autistic people.

Identifying Medications Underlying Communication Atypicalities in Psychotic and Affective Disorders: A Pharmacovigilance Study Within the FDA Adverse Event Reporting System

PURPOSE

Communication atypicalities are considered promising markers of a broad range of clinical conditions. However, little is known about the mechanisms and confounders underlying them. Medications might have a crucial, relatively unknown role both as potential confounders and offering an insight on the mechanisms at work. The integration of regulatory documents with disproportionality analyses provides a more comprehensive picture to account for in future investigations of communication-related markers. The aim of this study was to identify a list of drugs potentially associated with communicative atypicalities within psychotic and affective disorders.

METHOD

We developed a query using the Medical Dictionary for Regulatory Activities to search for communicative atypicalities within the FDA Adverse Event Reporting System (updated June 2021). A Bonferroni-corrected disproportionality analysis (reporting odds ratio) was separately performed on spontaneous reports involving psychotic, affective, and non-neuropsychiatric disorders, to account for the confounding role of different underlying conditions. Drug-adverse event associations not already reported in the Side Effect Resource database of labeled adverse drug reactions (unexpected) were subjected to further robustness analyses to account for expected biases.

RESULTS

A list of 291 expected and 91 unexpected potential confounding medications was identified, including drugs that may irritate (inhalants) or desiccate (anticholinergics) the larynx, impair speech motor control (antipsychotics), or induce nodules (acitretin) or necrosis (vascular endothelial growth factor receptor inhibitors) on vocal cords; sedatives and stimulants; neurotoxic agents (anti-infectives); and agents acting on neurotransmitter pathways (dopamine agonists).

CONCLUSIONS

We provide a list of medications to account for in future studies of communication-related markers in affective and psychotic disorders. The current test case illustrates rigorous procedures for digital phenotyping, and the methodological tools implemented for large-scale disproportionality analyses can be considered a road map for investigations of communication-related markers in other clinical populations.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.23721345.

Prosodic signatures of ASD severity and developmental delay in preschoolers

Atypical prosody in speech production is a core feature of Autism Spectrum Disorder (ASD) that can impact everyday life communication. Because the ability to modulate prosody develops around the age of speech acquisition, it might be affected by ASD symptoms and developmental delays that emerge at the same period. Here, we investigated the existence of a prosodic signature of developmental level and ASD symptom severity in a sample of 74 autistic preschoolers. We first developed an original diarization pipeline to extract preschoolers' vocalizations from recordings of naturalistic social interactions. Using this novel approach, we then found a robust voice quality signature of ASD developmental difficulties in preschoolers. Furthermore, some prosodic measures were associated with one year later outcome in participants who had not acquired speech yet. Altogether, our results highlight the potential benefits of automatized diarization algorithms and prosodic metrics for digital phenotyping in psychiatry, helping clinicians establish early diagnosis and prognosis.

Different in different ways: A network-analysis approach to voice and prosody in Autism Spectrum Disorder

The current study investigated whether the difficulty in finding group differences in prosody between speakers with autism spectrum disorder (ASD) and neurotypical (NT) speakers might be explained by identifying different acoustic profiles of speakers which, while still perceived as atypical, might be characterized by different acoustic qualities. We modelled the speech from a selection of speakers (N = 26), with and without ASD, as a network of nodes defined by acoustic features. We used a community-detection algorithm to identify clusters of speakers who were acoustically similar and compared these clusters with atypicality ratings by naïve and expert human raters. Results identified three clusters: one primarily composed of speakers with ASD, one of mostly NT speakers, and one comprised of an even mixture of ASD and NT speakers. The human raters were highly reliable at distinguishing speakers with and without ASD, regardless of which cluster the speaker was in. These results suggest that community-detection methods using a network approach may complement commonly-employed human ratings to improve our understanding of the intonation profiles in ASD.

Differences in speech articulatory timing and associations with pragmatic language ability in autism

Background

Speech articulation difficulties have not traditionally been considered to be a feature of Autism Spectrum Disorder (ASD). In contrast, speech prosodic differences have been widely reported in ASD, and may even be expressed in subtle form among clinically unaffected first-degree relatives, representing the expression of underlying genetic liability. Some evidence has challenged this traditional dichotomy, suggesting that differences in speech articulatory mechanisms may be evident in ASD, and potentially related to perceived prosodic differences. Clinical measurement of articulatory skills has traditionally been phoneme-based, rather than by acoustic measurement of motor control. Subtle differences in articulatory/motor control, prosodic characteristics (acoustic), and pragmatic language ability (linguistic) may each be contributors to differences perceived by listeners, but the interrelationship is unclear. In this study, we examined the articulatory aspects of this relationship, in speech samples from individuals with ASD and their parents during narration.

Method

Using Speechmark® analysis, we examined articulatory landmarks, fine-grained representations of articulatory timing as series of laryngeal and vocal-tract gestures pertaining to prosodic elements crucial for conveying pragmatic information.

Results

Results revealed articulatory timing differences in individuals with ASD but not their parents, suggesting that although potentially not influenced by broader genetic liability to ASD, subtle articulatory differences may indeed be evident in ASD as the recent literature indicates. A follow-up path analysis detected associations between articulatory timing differences and prosody, and subsequently, pragmatic language ability.

Conclusion

Together, results suggest a complex relationship where subtle differences in articulatory timing may result in atypical acoustic signals, and serve as a distal mechanistic contributor to pragmatic language ability ASD.

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development

BACKGROUND

Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children.

AIMS

After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations.

METHODS

We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors.

RESULTS

Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children.

CONCLUSIONS

We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.

Cross-linguistic patterns of speech prosodic differences in autism: A machine learning study

Differences in speech prosody are a widely observed feature of Autism Spectrum Disorder (ASD). However, it is unclear how prosodic differences in ASD manifest across different languages that demonstrate cross-linguistic variability in prosody. Using a supervised machine-learning analytic approach, we examined acoustic features relevant to rhythmic and intonational aspects of prosody derived from narrative samples elicited in English and Cantonese, two typologically and prosodically distinct languages. Our models revealed successful classification of ASD diagnosis using rhythm-relative features within and across both languages. Classification with intonation-relevant features was significant for English but not Cantonese. Results highlight differences in rhythm as a key prosodic feature impacted in ASD, and also demonstrate important variability in other prosodic properties that appear to be modulated by language-specific differences, such as intonation.

Vocal markers of autism: Assessing the generalizability of machine learning models

Machine learning (ML) approaches show increasing promise in their ability to identify vocal markers of autism. Nonetheless, it is unclear to what extent such markers generalize to new speech samples collected, for example, using a different speech task or in a different language. In this paper, we systematically assess the generalizability of ML findings across a variety of contexts. We train promising published ML models of vocal markers of autism on novel cross-linguistic datasets following a rigorous pipeline to minimize overfitting, including cross-validated training and ensemble models. We test the generalizability of the models by testing them on (i) different participants from the same study, performing the same task; (ii) the same participants, performing a different (but similar) task; (iii) a different study with participants speaking a different language, performing the same type of task. While model performance is similar to previously published findings when trained and tested on data from the same study (out-of-sample performance), there is considerable variance between studies. Crucially, the models do not generalize well to different, though similar, tasks and not at all to new languages. The ML pipeline is openly shared. Generalizability of ML models of vocal markers of autism is an issue. We outline three recommendations for strategies researchers could take to be more explicit about generalizability and improve it in future studies. LAY SUMMARY: Machine learning approaches promise to be able to identify autism from voice only. These models underestimate how diverse the contexts in which we speak are, how diverse the languages used are and how diverse autistic voices are. Machine learning approaches need to be more careful in defining their limits and generalizability.

An Examination of Articulatory Precision in Autistic Children and Adults

PURPOSE

According to the speech attunement framework, autistic individuals lack the ability and/or motivation to "tune up" their speech to the same level of precision as their neurotypical peers. However, previous studies exploring the articulatory patterns of autistic individuals have yielded disparate findings. One reason contrasting conclusions exist may be because studies have relied on perceptual measures of articulation. Here, we use an objective acoustic measure of articulatory precision to explore the articulatory patterns of autistic children and adults.

METHOD

This was a retrospective analysis of an existing corpus of 900 recorded speech samples taken from 30 adult and 30 child participants across two different population groups: autistic individuals (autism spectrum disorder [ASD] group) and neurotypical individuals (neurotypical [NT] group). Articulatory precision scores were calculated using an automated metric that compares observed acoustics to the expected acoustics for each phoneme production. Linear mixed-effects models were used to compare the articulatory precision scores across population group (i.e., ASD group vs. NT group) and to see if these differences were moderated by age group (i.e., children vs. adult).

RESULTS

The speech of autistic individuals was characterized by reduced articulatory precision relative to their neurotypical peers. This pattern was not significantly moderated by age, indicating it occurred in both the children and adult groups.

CONCLUSIONS

Our preliminary findings indicate that imprecise articulation may be a characteristic of the speech of autistic individuals in both childhood and adulthood. These findings are in line with predictions posited by the speech attunement framework. Given the current lack of speech markers for this clinical population and the importance of speech quality in the social integration of autistic individuals, our results advance articulatory precision as a viable and important target for future research.

A systematic review and Bayesian meta-analysis of the development of turn taking in adult-child vocal interactions

Fluent conversation requires temporal organization between conversational exchanges. By performing a systematic review and Bayesian multi-level meta-analysis, we map the trajectory of infants' turn-taking abilities over the course of early development (0 to 70 months). We synthesize the evidence from 26 studies (78 estimates from 429 unique infants, of which at least 152 are female) reporting response latencies in infant-adult dyadic interactions. The data were collected between 1975 and 2019, exclusively in North America and Europe. Infants took on average circa 1 s to respond, and the evidence of changes in response over time was inconclusive. Infants' response latencies are related to those of their adult conversational partners: an increase of 1 s in adult response latency (e.g., 400 to 1400 ms) would be related to an increase of over 1 s in infant response latency (from 600 to 1857 ms). These results highlight the dynamic reciprocity involved in the temporal organization of turn-taking. Based on these results, we provide recommendations for future avenues of enquiry: studies should analyze how turn-by-turn exchanges develop on a longitudinal timescale, with rich assessment of infants' linguistic and social development.