Variation In Speech Research Articles

Speech profile in different clinical PSP phenotypes: an acoustic-perceptual study.

Progressive supranuclear palsy (PSP) is a neurodegenerative disease with pathological hallmarks and different clinical presentations. Recently, the Movement Disorder Society (MDS) promoted a new classification; specific combinations of the core clinical features identify different phenotypes, including PSP with Richardson's syndrome (PSP-RS) and PSP with predominant parkinsonism (PSP-P). Since speech disorders are very common in PSP, they were included in the MDS-PSP criteria as a supportive clinical feature in the form of hypokinetic, spastic dysarthria. However, little is known about how dysarthria presents across the different PSP variants. The aim of the present study is to evaluate the presence of differences in speech profile in a cohort of PSP-RS and PSP-P patients diagnosed according to the MDS-PSP criteria. Each patient underwent a neurological evaluation and perceptual and acoustic analysis of speech. Disease severity was rated using the Natural History and Neuroprotection in Parkinson plus syndromes-Parkinson plus scale (NNIPPS-PPS), including global score and sub-scores. Twenty-five patients (mean disease duration [standard deviation] = 3.32 [1.79]) were classified as PSP-RS, while sixteen as PSP-P (mean disease duration [standard deviation] = 3.47 [2.00]). These subgroups had homogeneous demographical and clinical characteristics, including disease severity quantified by the NNIPPS-PPS total score. Only the NNIPPS-PPS oculomotor function sub-score significantly differed, being more impaired in PSP-RS patients. No significant differences were found in all speech variables between the two groups. Speech evaluation is not a distinguishing feature of PSP subtypes in mid-stage disease.

The Geographical and Social Stratification of Judeo-Georgian

Abstract This article focuses on the variation found within Judeo-Georgian as it correlates with predetermined geographical and social categories and explores the changes it underwent as spoken by the small Jewish community remaining in Georgia and, later, as a consequence of contacts with other languages, in a new linguistic environment in Israel. The research is based on the theories and methods of variationist sociolinguistics and linguistic anthropology. Social and geographical factors were instrumental in shaping linguistic variation in Judeo-Georgian as one of the key identity markers of Georgian Jews. Geographical, social, and religious dimensions of Judeo-Georgian are discussed in relation to linguistic variables. The research builds on Sarah Bunin Benor’s (2008) distinctive linguistic repertoire approach to Jewish languages. The varieties of Judeo-Georgian spoken in Georgia were based on local/regional dialects but differed from them through the use of Hebraisms/Aramaisms, displaced dialectisms, and archaisms. Upper-class Jews largely avoided using Judeo-Georgian, middle-class Jews used it in certain speech situations, and for lower-class Jews, it was the only means of communication. Regional and social peculiarities of Judeo-Georgian, as spoken in different parts of Georgia, as well as the changes caused by immigration, are manifest in the speech varieties spoken by Georgian Jewry in Israel.

Variation in Non-native Speech: How Far Do Non-native Speakers Replicate Target Constraints on Variation? A Novel Approach

This paper introduces a new framework to analyze how non-native speakers adhere to native-speaker norms of variation in contact settings. The author focuses on a well-established phonological variable in both native and contact-induced varieties of English: consonant cluster reduction. This process involves either dropping or maintaining a final coronal stop (t,d) in a consonant cluster in words such as "mind" and "west." The paper uses standard variationist methodologies to establish the constraints on consonant cluster reduction in a native-speaker group (Wellingtonian English) and a non-native speaker sample (Arab migrants to Wellington). The study then compares these constraints, identifying any changes introduced by non-native speakers. The results show that the non-native group is highly attuned to dialect-specific aspects of variation and demonstrates a deletion rate close to native speakers. Additionally, they exhibit a strong transfer of target articulatory constraints related to consonant cluster reduction and acquire the social cues associated with this variation. Interestingly, these patterns of variation in non-native speech are consistent across similar non-native groups, irrespective of first language, proficiency in English, and the complexity of the target constraints on variation.

Spontaneous speech: a robust measurement before, during and after awake brain surgery in patients with glioma

Background Patients with glioma often report language complaints with devastating effect on daily life. Analysing spontaneous speech can help to understand underlying language problems. Spontaneous speech monitoring is also of importance during awake brain surgery: it can guide tumour resection and contributes to maintaining language function. We aimed to investigate the spontaneous speech of patients with glioma in the perioperative period and the additional value of spontaneous speech analyses compared to standardised language testing. Methods We elicited and transcribed spontaneous speech of eight patients with glioma elected for awake brain surgery preoperatively, intraoperatively and 2.0–3.5 months postoperatively. Linguistic errors were coded. Type Token Ratio, Mean Length of Utterance of words, minimal utterances, and errors were extracted from the transcriptions. Patients were categorised based on total error patterns: stable, decrease or increase during surgery. Reliable Change Index scores were calculated for all spontaneous speech variables to objectify changes between time points. Language performance on language tests was compared to spontaneous speech variables. Results Most errors occurred in lexico-syntax, followed by phonology/articulation, syntax, and semantics. The predominant errors were Repetitions, Self-corrections, and Incomplete sentences. Most patients remained stable over time in almost all spontaneous speech variables, except in Incomplete sentences, which deteriorated in most patients postoperatively compared to intraoperatively. Some spontaneous speech variables (total errors, MLUw, TTR) gave more information on language change than a standard language test. Conclusions While the course of spontaneous speech over time remained relatively stable in most patients, Incomplete sentences seems to be a robust marker of language difficulties patients with glioma. These errors can be prioritised in spontaneous speech analysis to save time, especially to determine intra- to postoperative deterioration. Importantly, spontaneous speech analyses can give more information on language change than standardised language testing and should therefore be used in addition to standardised language tests.

Dual-stream Noise and Speech Information Perception based Speech Enhancement

In real-world scenarios, dynamic ambient noise often degrades speech quality, highlighting the need for advanced speech enhancement techniques. Traditional methods, which rely on static embeddings as auxiliary features, struggle to address the complexities of varying noise conditions. To overcome this, we propose a Dual-stream Noise and Speech Information Perception (DNSIP) approach that dynamically detects and processes both noise and speech through innovative information extraction and suppression mechanisms. Initially, non-speech segments predominantly contain environmental noise, while speech segments carry information about the intended speaker. To handle this dynamic nature, real-time voice activity detection (VAD) is employed to accurately differentiate between speech and noise components. Building on VAD estimates, we propose an innovative information extraction framework that selectively extracts relevant noise and speech features from the noisy input, establishing a dual-stream network for concurrent noise and speech learning. To account for the temporal and spectral variability of noise and speech, a frequency-sequence attention mechanism is integrated, enhancing the model’s ability to learn contextual and spectral dependencies. Additionally, an information suppression module is introduced to minimize cross-stream interference by attenuating noise within the speech stream and suppressing speech content within the noise stream. The derived noise and speech spectrograms are then utilized to formulate a minimum mean square error log-spectral amplitude (MMSE-LSA) estimator for robust speech enhancement. Experimental evaluations on the WSJ0 and VCTK+DEMAND datasets demonstrate that our DNSIP approach surpasses existing state-of-the-art methods, underscoring its efficacy in challenging acoustic environments.

Gender and age biases in the assessment of speech accuracy: A study of speech-language clinicians' ratings of /s/ accuracy.

Typically developing children assigned male at birth (AMAB) and children assigned female at birth (AFAB) produce the fricative /s/ differently: AFAB children produce /s/ with a higher spectral peak frequency. This study examined whether implicit knowledge of these differences affects speech-language pathologists'/speech and language therapists' (SLPs'/SLTs') ratings of /s/ accuracy, by comparing ratings made in conditions where SLPs/SLTs were blind to children's sex assigned at birth (SAB) to conditions in which they were told this information. SLPs (n = 95) varying in clinical experience rated the accuracy of word-initial /s/ productions (n = 87) of eight children with speech sound disorder in one of four conditions: one in which no information about the children was revealed, one in which children's SAB was revealed, one in which children's age was revealed, and one in which both were revealed. Despite there being no statistically significant differences between AFAB and AMAB children's /s/ production in researcher-determined accuracy or in one acoustic characteristic, spectral centroid, SLPs in all four conditions judged the /s/ productions of AFAB children as more accurate than AMAB children. Listeners were significantly less likely to judge the productions of AMAB children to be inaccurate in the conditions in which age or age and SAB were revealed. These effects were consistent across SLPs with greatly varying levels of clinical experience. Knowing or imputing children's age and SAB can affect ratings of /s/ accuracy. Clinicians should be mindful of these potential effects. Future research should understand how expectations about sociolinguistic variation in speech affect appraisals of their speech and language. What is already known on the subject Adult men and women produce /s/ differently. A consensus is that these differences reflect sociolinguistic gender marking, rather than being the passive consequence of vocal-tract differences. Recent studies have shown that children assigned female at birth (AFAB) and those assigned male at birth (AMAB) produce /s/ differently in ways that mirror the differences between adult men and women, and which presumably reflect gender marking. What this paper adds to existing knowledge We asked whether US-based speech-language pathologists' (SLPs) ratings of the accuracy of /s/ differ depending on whether they are rating an AFAB or an AMAB child, and whether these differences are greater in conditions in which people are told the sex assigned at birth of the child being rated. We found that SLPs were more likely to judge AFAB children's /s/ productions to be more accurate than AMAB children's, even though the productions from the AMAB and AFAB children that were used as stimuli were matched for accuracy as determined by trained researchers. What are the clinical implications of this work? SLPs/speech-language therapists should be sensitive to the influence of social variables when assessing /s/. SLPs/speech-language therapists might rate children's productions differently depending on whether they believe they are rating an AFAB or an AMAB child.

Zygosity Effects on Human Voice: Fundamental Frequency Analysis of Brazilian Twins' Speech.

Voice production can be influenced by interindividual variations related to genetic, physiological, behavioral, and several environmental factors. Here we examined the effect of zygosity on speaking fundamental frequency (F0) statistical descriptors. Our aims were: (1) to determine whether the genetic similarity between monozygotic (MZ) and dizygotic (DZ) twins affects F0 characteristics, and (2) to quantify the contribution of genetic factors to these characteristics. The study involved 79 same-sex twin pairs of Brazilian Portuguese speakers, comprising 65 MZ and 14 DZ twins, aged 18 to 66 years (31.7 ± 11.6 years), with 21 male and 58 female pairs. Participants were recorded while uttering a greeting phrase and the Brazilian Portuguese version of the 'Happy Birthday to You' song. Speech segments were analyzed using Praat free software, and F0 measures were automatically extracted in both Hertz and semitone scales. Statistical descriptors, including centrality, dispersion, and extreme values of F0 were examined, and the ACE model (i.e., total genetic effects, A; shared environmental influences, C; and nonshared environmental influences, E) was employed to estimate the additive effect;ts of monozygosity. As anticipated, we observed a zygosity effect on several F0 parameters, with more similarity between MZ twins compared to DZ twins. We discuss the genetic influences on F0 parameters and the absence of a monozygosity effect in two of them. Additionally, we briefly address potential biases associated with the selected measurement scale for statistical modeling. Finally, we explore the influence of genetic factors on F0 patterns, as well as environmental, life history and linguistic factors, particularly concerning F0 variation in speech.

Longitudinal follow-up of hearing, speech, and language skills in 6-year-old children with congenital moderate hearing loss

ObjectivesChildren born with moderate hearing loss present with speech and language outcomes at both ends of the spectrum. To explore reasons for this, the objective of this study was to follow up a group of children born with moderate sensorineural hearing loss at 6 years of age (n=7) by investigating their outcomes in hearing, speech, and language development from time point of hearing aid fitting at 6 months. Another objective was to investigate the relationship between earlier outcomes on precursing variables to the current status in auditory, speech and language development. MethodEarlier data from a project with the same participants of auditory variables, speech, and language development were compared to the current study outcomes at 6 years of age. Children in this study performed standardized tests of phonology (SVANTE), expressive vocabulary (BNT), and speech-in-noise test (Hagerman´s sentences). Parents reported on their child´s functional auditory performance in everyday life (PEACH), and demographics and general development (questionnaire). Etiology and frequency of speech and language-directed intervention from time point of diagnosis to 6 years of age were collected through medical journals. ResultsHearing levels were stable over time in all children but one, who had received bilateral cochlear implants. Performance on speech-in-noise testing varied in aided condition (-0.8 to 8, mean 2.65, SD 3.09) and unaided condition (7.2 dB to 21.2 dB, mean 12.06, SD 4.82). Scores on the PEACH indicated further review in four of the seven children. Mean group score on consonant proficiency had increased from 3 to 6 years of age and were within age norms. Vocabulary scores were below the norms of children with typical hearing. Outcomes on vocabulary measures at 2.5 years years showed strong correlations that were significant to scores on the BNT at 6 years of age (r = 0.87, p = 0.05). Correlations between hours of hearing aid use and vocabulary was not significant at 6 years of age. The frequency of intervention sessions in the first 6 years varied between participants (4 to 55, mean 19.1, SD 17.1). ConclusionDespite homogeneous hearing and other background variables in the participants from birth, large individual variations in speech and language outcomes at 6 years of age were found. Considering the many factors involved that impact the development of children with moderate hearing loss, the results suggest that monitoring early precursors in auditory, speech and language development may be helpful in setting commensurate goals for each child. Detecting additional conditions that may pose challenges in future speech and language as early as possible is important. There is ample room for improvement in terms of increasing the frequency of intervention for children with moderate hearing loss and their families.

Late feature fusion using neural network with voting classifier for Parkinson’s disease detection

Parkinson’s disease (PD) is classified as a neurological, progressive illness brought on by cell death in the posterior midbrain. Early PD detection will assist doctors in reducing the disease’s consequences. A collection of skilled models that may be applied to regression as well as classification is known as artificial intelligence (AI). PD can be detected using a variety of dataset formats, including text, speech, and picture datasets. For the purpose of classifying Parkinson’s disease, this study suggests merging deep with machine learning recognition approaches. The three primary components of the suggested approach are designed to enhance the accuracy of Parkinson’s disease early diagnosis. These sections cover the topics of categorising, combining, and separating. Convolutional Neural Networks (CNN) as well as attention procedures are used to create feature extractors. The related motion signals are fed to a combination of convolutional neural network and long-short-memory model for feature extraction. Besides, for the classification of patients from non-suffers of Parkinson’s disease, Random Forest, Logistic Regression, Support Vector Machine, Extreme Boot Classifier, and voting classifier were used. Our result shows that for the PD handwriting and related motion datasets, using the proposed CNN with an attention and voting classifier yields 99.95% accuracy, 99.99% precision, 99.98% sensitivity, and 99.95% F1-score. Based on these results, it is warranted to conclude that the proposed methodology of feature extraction from photos of handwriting and relating motor symptoms, fusing of those features, and following it with a voting classifier yields excellent results for PD classification.

Capturing chronological variation in L2 speech through lexical measurements and regression analysis

This study aims to bridge gaps in current research by analyzing a longitudinal spoken learner corpus of low-proficiency English learners. We investigated the chronological variation in lexical measurements in second language (L2) speaking production, focusing on data from 104 low-proficiency learners elicited eight times over 23 months. Our findings show that measures such as the number of different words and type-token ratio are effective indicators of L2 speaking development, whereas the use of sophisticated vocabulary was not significantly correlated with learning duration. These results suggest that in the early stages of L2 acquisition, speaking skills are influenced primarily by lexical variation. This finding underscores the importance of lexical variation as a key factor in novice-level L2 speaking proficiency.

HEAR-MHE study: Automated speech analysis identifies minimal hepatic encephalopathy and may predict future overt hepatic encephalopathy.

Hepatic encephalopathy (HE) is a major cause of poor quality of life in patients with cirrhosis. A simple diagnostic test to identify minimal HE (MHE) and predict future overt HE (OHE) is lacking. We aimed to evaluate if analysis of speech patterns using a modern speech platform: 1) correlates with validated HE tests, 2) correlates with MHE, and 3) predicts future OHE. In a two-center prospective cohort study of 200 outpatients with cirrhosis and 50 controls, patients underwent baseline speech recording and validated HE diagnostic testing with psychometric HE score (PHES). Patients were followed for 6 months to identify episodes of OHE. 752 speech variables were extracted using an automated speech analysis platform, reflecting the acoustic, lexical, and semantic aspects of speech. Patients with cirrhosis were median 63 years old (IQR 54, 68), 49.5% (99) were female. Over 100 speech variables were significantly associated with PHES (p <0.05 with FDR adjustment). A three-variable speech model (two acoustic, one speech tempo variable) was similar to animal naming test in predicting MHE (AUC 0.76 vs. 0.69; p=0.11). Adding age and MELD-Na improved accuracy of the speech model (AUC: 0.82). A combined clinical-speech model ("HEAR-MHE model") predicted time to OHE with a concordance of 0.74 (p=0.06). Automated speech analysis highly correlated with validated HE tests, associated with MHE, and may predict future OHE. Future research is needed to validate this tool and to understand how it can be implemented in clinical practice.

Effective Communication in Action: Unveiling Teacher Speech Acts in Indonesian Language Education

The Community Service (PKM) aims to analyze the speech acts of teachers used when teaching Indonesian subjects to students at Tinggimoncong State Elementary School, Gowa Regency, South Sulawesi Province. This service was carried out by involving Indonesian language teachers as partners in exploring the variety of speech acts used in delivering material in class. This service applied classroom observations, interviews, and recordings as data collection techniques. Data analysis used a qualitative approach, specifically a systematic coding of the observed interactions, to identify the dominant speech acts used by teachers when delivering the material. The results of the service show that the variety of speech acts used by teachers during Indonesian language learning are directive speech acts used to give instructions to students, expressive speech acts used to build emotional relationships with students, commissive speech acts, and declarative speech acts appear in explaining and giving teacher assignments to students. Teachers use assertive speech acts to express, state, and inform about subjects taught in class. This PKM activity also provides training to teachers on the application of speech acts that can increase the effectiveness of learning in the classroom. Implementing the findings positively impacts the communication skills of teachers teaching subjects, mainly Indonesian.

Prosody matters: Preserved prominence marking strategies in people with Parkinson's disease independent of motor status.

While many studies focus on segmental variation in Parkinsonian speech, little is known about prosodic modulations reflecting the ability to adapt to communicative demands in people with Parkinson's disease (PwPD). This type of prosodic modulation is important for social interaction, and it involves modifications in speech melody (intonational level) and articulation of consonants and vowels (segmental level). The present study investigates phonetic cues of prosodic modulations with respect to different focus structures in mild dysarthric PwPD as a function of levodopa. Acoustic and kinematic speech parameters of 25 PwPD were assessed in two motor conditions. Speech production data from PwPD were collected before (medication-OFF) and after levodopa intake (medication-ON) by means of 3-D electromagnetic articulography. On the acoustic level, intensity, pitch, and syllable durations were analyzed. On the kinematic level, movement duration and amplitude were investigated. Spatio-temporal modulations of speech parameters were examined and compared across three different prosodic focus structures (out-of-focus, broad focus, contrastive focus) to display varying speech demands. Overall, levodopa had beneficial effects on motor performance, speech loudness, and pitch modulation. Acoustic syllable durations and kinematic movement durations did not change, revealing no systematic effects of motor status on the temporal domain. In contrast, there were spatial modulations of the oral articulators: tongue tip movements were smaller and lower lip movements were larger in amplitude under levodopa, reflecting a more agile and efficient articulatory movement under levodopa. Thus, respiratory-phonatory functions and consonant production improved, while syllable duration and tongue body kinematics did not change. Interestingly, prominence marking strategies were comparable between the medication conditions under investigation, and in fact, appear to be preserved in mild dysarthric PwPD.

Tempo variation in regional speech (based on northern and southern English dialects)

Tempo variation in regional speech (based on northern and southern English dialects)

Confessional Component of Urbanonymy in Lexicographic Interpretation

This article addresses the issues of enhancing the lexicographic representation of confessionally marked urbanonyms. The objective of the study is to substantiate parametric models for dictionary entries that allow for a comprehensive presentation of the confessional component of urbanonymy in both culturalhistorical and functional aspects. The research material is drawn from the database of the Experimental Laboratory of Educational Lexicography at Pskov State University, which contains 3,000 urbanonyms, including more than 200 ecclesionims (official, colloquial, and slang), forming the core of the urbanonymconfessionalism dataset. Through structuralsemantic and contextual analysis, the study identifies the denotative correlations, lexical composition of these urbanonyms, and various types of their variations in contemporary speech. Historical-etymological analysis aids in uncovering the motivations behind nomination. The method of linguocultural interpretation is employed in developing the commentary section of the dictionary entry. Lexicographic construction techniques are utilized in creating an improved model for entries in a general alphabetical urbanonym dictionary and an innovative discourse-type entry for an urbanonym guide dictionary. Samples of dictionary entries with accompanying comments are presented.

Speaker Recognition: A Comparative analysis Between Deep Learning and Non-Deep Learning Methodologies

This work carries out a comparative study of two methodologies for speaker recognition. It is Deep Learning (DL) and Vector Quantization (VQ). The key area in biometric au-thentication systems involves speaker recognition. This requires durable and efficient algorithms. The aim is to ensure a high accuracy and reliability. The study delves into a deep neural network (DNN) model implementation. It leverages advanced feature extraction. It uses pattern recognition capabilities which are in DL. The study also examines a traditional VQ approach. This method makes use of codebook generation and quantization for speaker ID. Extensive experimentation was done on standard datasets. The project evaluates the performance of two methods. It compares accuracy. It assesses computational complexity. It does so for noise and for variations in speech. The findings of this analysis reveal the strengths and limitations of each technique. Looking at their practical applicability in real-world scenarios provides insights. The comparative results of these techniques aim to guide future developments. This concerns speaker recognition systems - particularly their potential for enhanced performance.

Perception of Mandarin tones across different phonological contexts by native and tone-naive listeners

Coarticulation is a type of speech variation where sounds take on phonetic properties of adjacent sounds. Listeners generally display perceptual compensation, attributing coarticulatory variation to its source. Mandarin Chinese lexical tones are coarticulated based on surrounding tones. We tested how L1-Mandarin and naive listeners compensate for tonal coarticulation using a paired discrimination task. L1 listeners showed greater perceptual sensitivity to tonal differences than tone-naive listeners. Yet, both L1 and tone-naive listeners showed differences in sensitivity to differently-coarticulated versions of the rising tone presented in the same tonal context. In different tonal contexts, both groups showed similar patterns of perceptual compensation for tonal coarticulation. Thus, although L1 and naive Mandarin listeners show different sensitivities to tonal variation, they display similar compensatory patterns for tonal coarticulation.

A Critical Pragmatic Analysis of some Selected Songs of Ilerioluwa Oladimeji Aloba (MohBad)

This study investigates a critical pragmatic analysis of some selected songs of Ilerioluwa Oladimeji Aloba (MohBad). Specifically, the study focuses on Speech Act analysis of the selected songs and ascertains the ways speech acts are expressed in these songs. Two research questions: What speech acts are represented in Mohbad’s songs? And to what extent are the tenets of speech acts expressed in Mohbad’s Songs? guided this study. The theory of the Pragmatic Act introduced by Jacob Mey (2001) is used as the theoretical foundation of the study. The research is categorized as descriptive qualitative research. The data for the study consists of selected songs of Ilerioluwa Oladimeji Aloba: ‘Ask About Me’, ‘Feel Good’ and ‘Peace’. These songs were selected based on the complex and multifaceted narratives which mirror the songwriter’s life and struggles. The songs’ lyrics are made available and readily accessed from music streaming platforms like Spotify, Apple Music, and YouTube for lyric references. The findings of the study reveal that the lyrics of Aloba’s songs show a variety of speech acts such as assertions, declarations, interrogatives, expressive utterances and commission, all of which help reveal his journey from hardship to fame and how he accomplished acceptance, his challenges and resilience, his defiance and self-assuredness; and his boldness in engaging his listeners. These have revealed the depth of meaning and intention of the songwriter beyond the lyrics of the songs.

Perception and adaptation of receptive prosody in autistic adolescents

A fundamental aspect of language processing is inferring others’ minds from subtle variations in speech. The same word or sentence can often convey different meanings depending on its tempo, timing, and intonation–features often referred to as prosody. Although autistic children and adults are known to experience difficulty in making such inferences, the science remains unclear as to why. We hypothesize that detail-oriented perception in autism may interfere with the inference process if it lacks the adaptivity required to cope with the variability ubiquitous in human speech. Using a novel prosodic continuum that shifts the sentence meaning gradiently from a statement (e.g., “It’s raining”) to a question (e.g., “It’s raining?”), we have investigated the perception and adaptation of receptive prosody in autistic adolescents and two groups of non-autistic controls. Autistic adolescents showed attenuated adaptivity in categorizing prosody, whereas they were equivalent to controls in terms of discrimination accuracy. Combined with recent findings in segmental (e.g., phoneme) recognition, the current results provide the basis for an emerging research framework for attenuated flexibility and reduced influence of contextual feedback as a possible source of deficits that hinder linguistic and social communication in autism.

Noise-Robust Automatic Speech Recognition: A Case Study for Communication Interference

An Automatic Speech Recognition (ASR) System is a software tool that converts a speech audio waveform into its corresponding text transcription. ASR systems are usually built using Artificial Intelligence techniques, particularly Machine Learning algorithms like Deep Learning, to address the multi-faceted complexity and variability of human speech. This allows these systems to learn from extensive speech datasets, adapt to several languages and accents, and continuously improve their performance over time, making them each time more versatile and effective in their purpose of transcribing spoken language to text. Much in the same way, we argue that the noises commonly present in the different environments also need to be explicitly dealt with, and, when possible, modeled within specific datasets with proper training. Our motivation comes from the observation that noise removal techniques (commonly called denoising), are not always fully (and generically) efficient. For instance, noise degeneration due to communication interference, which is almost always present in radio transmissions, has peculiarities that a simple mathematical formulation cannot model. This work presents a modeling technique composed of an augmented dataset-building approach and a profile identifier that can be used to build ASRs for noisy environments that perform similarly to those used in noise-free environments. As a case study, we developed a specific ASR for the interference noise in radio transmissions with its specific dataset, while comparing our results with other state-of-the-art work. As a result, we report a Character Error Rate value of 0.3163 for the developed ASR under several different noise conditions.