Search Results (262)

Background/Objectives: Children with Autism Spectrum Disorder (ASD) often display heightened sensitivity to simple auditory stimuli, but have difficulty discriminating and integrating multiple phonological features (segmental: consonants and vowels; suprasegmental: lexical tones) at the syllable level, which negatively impacts their communication. This study aims to investigate the neural basis of segmental, suprasegmental and combinatorial speech processing challenges in Mandarin-speaking children with ASD compared with typically developing (TD) peers. Methods: Thirty children with ASD and thirty TD peers will complete a multi-feature oddball paradigm to elicit auditory ERP during passive listening. Stimuli include syllables with single (e.g., vowel only), dual (e.g., vowel + tone), and triple (consonant + vowel + tone) phonological deviations. Neural responses will be analyzed using temporal principal component analysis (t-PCA) to isolate overlapping ERP components (early/late MMN), and representational similarity analysis (RSA) to assess group differences in neural representational structure across feature conditions. Expected Outcomes: We adopt a dual-framework approach to hypothesis generation. First, from a theory-driven perspective, we integrate three complementary models, Enhanced Perceptual Functioning (EPF), Weak Central Coherence (WCC), and the Neural Complexity Hypothesis (NCH), to account for auditory processing in ASD. Specifically, we hypothesize that ASD children will show enhanced or intact neural discriminatory responses to isolated segmental deviations (e.g., vowel), but attenuated or delayed responses to suprasegmental (e.g., tone) and multi-feature deviants, with the most severe disruptions occurring in complex, multi-feature conditions. Second, from an empirically grounded, data-driven perspective, we derive our central hypothesis directly from the mismatch negativity (MMN) literature, which suggests reduced MMN amplitudes (with the exception of vowel deviants) and prolonged latencies accompanied by a diminished left-hemisphere advantage across all speech feature types in ASD, with the most pronounced effects in complex, multi-feature conditions. Significance: By testing alternative hypotheses and predictions, this exploratory study will clarify the extent to which speech processing differences in ASD reflect cognitive biases (local vs. global, per EPF/WCC/NCH) versus speech-specific neurophysiological disruptions. Findings will advance our understanding of the sensory and integrative mechanisms underlying communication difficulties in ASD, particularly in tonal language contexts, and may inform the development of linguistically tailored interventions. Full article

Background: This systematic review investigates how different surgical techniques influence speech outcomes in children with cleft palate, focusing on the effectiveness of key palatoplasty methods and the timing of surgery on vocal function. Methods: A thorough search of the PubMed, Scopus, and Web of Science databases was conducted for studies published between 2014 and 2024, including clinical research reporting speech results after palatal repair, with bias assessed using the ROBINS tool. Additionally, two clinical cases are presented to demonstrate the practical application of the surgical approaches. Results: Analysis of fourteen studies revealed that modified Z-plasty and V-Y procedures enhance soft palate mobility and reduce hypernasality, although they require advanced surgical skills. Early closure of the hard palate, performed within the first year of life, was linked to improved consonant articulation compared to later surgeries. No significant differences were found between single-stage and two-stage repairs, but surgeon experience emerged as a crucial factor influencing outcomes. Conclusions: Overall, both the surgical technique selected and the timing of intervention play important roles in optimizing speech development in children affected by cleft palate. Full article

Extrapyramidal symptoms encompass features of Parkinsonism, including bradykinesia, cogwheel rigidity, and resting tremors, which contribute to motor impairments hindering handwriting and speech. In this study, we analyzed voice data captured using a voice sensor setup from 94 patients exhibiting varying levels of EPS and 30 unaffected controls. Each participant provided 13 recordings of repeated vowel and consonant sounds. The Drug-Induced Extrapyramidal Side Effect Scale and Glasgow Antipsychotic Side Effect Scales were used when grading patients into mild, moderate, and severe extrapyramidal symptoms, both administered by trained clinicians. To develop an objective assessment tool, we employed a transfer learning approach using a DenseNet architecture for feature extraction and classification. Its architecture enables the hierarchical concatenation of features at each layer. In this study, we identified that key acoustic features, MFCC, chroma, and spectral contrast vary significantly with the severity of extrapyramidal symptoms. Based on these findings, we developed a DenseNet-based model capable of predicting extrapyramidal symptoms from voice data. This model can classify with an accuracy of 81.9% and a precision of 82.0%. To the best of our knowledge, this is the first study to introduce a voice-based model for assessing the severity of extrapyramidal symptoms. Full article

This research compares speech discrimination abilities between 17 children who are hard-of-hearing (CHH) and 13 children with normal hearing (CNH), aged 9 to 36 months, using either a conditioned head turn (CHT) or condition play paradigm, for two phoneme pairs /ba-da/ and /sa-ʃa/. As CHH were tested in the aided and unaided conditions, CNH were also tested on each phoneme contrast twice to control for learning effects. When speech discrimination abilities were compared between CHH, with hearing aids (HAs), and CNH, there were no statistical differences observed in performance on stop consonant discrimination, but a significant statistical difference was observed for fricative discrimination performance. Among CHH, significant benefits were observed for /ba-da/ speech discrimination while wearing HAs, compared to the no HA condition. All CHH were early-identified, early amplified, and were enrolled in parent-centered early intervention services. Under these conditions, CHH demonstrated the ability to discriminate speech comparable to CNH. Additionally, repeated testing within 1-month did not result in a change in speech discrimination scores, indicating good test–retest reliability of speech discrimination scores. Finally, this research explored the question of infant/toddler listening fatigue in the behavioral speech discrimination task. The CHT paradigm included returning to a contrast (i.e., /a-i/) previously shown to be easier for both CHH and CNH to discriminate to examine if failure to discriminate /ba-da/ or /sa-ʃa/ was due to listening fatigue or off-task behavior. Full article

Most academic papers on Jordanian colloquial Arabic allophonic consonant variants have primarily examined their influence on the social status of speakers and their role in shaping linguistic prestige. However, there is a significant lack of research exploring the potential for manipulation and establishment of power through the deliberate use of consonantal variants by Jordanian speakers in Arabic. Using a variety of allophonic consonantal variants, this study investigates how speakers of Jordanian colloquial Arabic attempt to construct their discourse of power. The targeted phonemes in the current study were /q/, /θ/, /ð/, and /k/. Focus groups were used to gather data, which were then examined within the framework of Fairclough’s technologized discourse and thematic approaches. Twenty persons, 10 women and 10 men, ranging in age from 18 to 45 years, comprised each of the two groups. The duration of each focus group session was 50 min. Analysis of the data indicates that the presence of [q], [θ], [ð], and [k] allophones in Standard Arabic is restricted to particular social circumstances, such as official and scientific environments. This usage is a common trait among those who have received formal education and privileged social standing. The findings also reveal that participants strategically utilize the allophonic variants [g], [ʔ], [k], [t̪], [d̪], and [tʃ] to exert influence over interlocutors by demonstrating authority related to social identity, gender, and emotional state. This study intends to advance discussions on allophonic consonant variants in Jordanian colloquial Arabic by providing insights into their manipulative functions. Full article

In this research paper, we study symmetry groups, soliton solutions, and the dynamical behavior of the Ivancevic Option Pricing Model (IOPM). First, we find the Lie symmetries of the considered model; next, we use them to determine the corresponding symmetry groups. Then, we attempt to solve IOPM by means of two methods. We provide some wave solutions and give further details of the solution using 2D and 3D graphs. These results are interpreted as important clarifications in financial mathematics and deepen our understanding of the dynamics involved during the pricing of options. Secondly, the quasi-periodic behavior of the two-dimensional dynamical system and its perturbed system are plotted using Python software (Python 3.13.5 version). Various frequencies and amplitudes are considered to confirm the quasi-periodic behavior via the Lyapunov exponent, bifurcation diagram, and multistability analysis. These findings are particularly in consonance with current research that investigates IOPM as a nonlinear wave alternate for normal models and the importance of graphical representations in the understanding of financial derivative dynamics. We, therefore, hope to fill in the gaps in the literature that currently exist about the use of multi-solution methods and their effects on financial modeling through the employment of sophisticated graphical techniques. This will be helpful in discussing matters in the field of financial mathematics and open up new directions of investigation. Full article

Effective language processing relies on pattern detection. Spanish monolinguals predict verb tense through stress–suffix associations: a stressed first syllable signals present tense, while an unstressed first syllable signals past tense. Low-proficiency second language (L2) Spanish learners struggle to detect these associations, and we investigated whether they benefit from game-based training. We examined the effects of four variables on their ability to detect stress–suffix associations: three linguistic variables—verbs’ lexical stress (oxytones/paroxytones), first-syllable structure (consonant–vowel, CV/consonant–vowel–consonant, CVC), and phonotactic probability—and one learner variable—working memory (WM) span. Beginner English learners of Spanish played a digital game focused on stress–suffix associations for 10 days and completed a Spanish proficiency test (Lextale-Esp), a Spanish background and use questionnaire, and a Corsi WM task. The results revealed moderate gains in the acquisition of stress–suffix associations. Accuracy gains were observed for CV verbs and oxytones, and overall reaction times (RTs) decreased with gameplay. Higher-WM learners were more accurate and slower than lower-WM learners in all verb-type conditions. Our findings suggest that prosody influences word activation and that digital gaming can help learners attend to L2 inflectional morphology. Full article

This study investigates the initial consonant system of the Yongle Nanzang 永乐南藏, the second officially printed edition of the Chinese Buddhist canon of the Ming dynasty, and its relationship to the Qishazang 磧砂藏. Based on a digital and quantitative analysis of 27,832 phonetic entries—including Fanqie 反切 and Zhiyin 直音—we apply correlation coefficients (with significance tests), hierarchical clustering, and data mining methods. The results show the following: (1) In the labial series, contrasts between aspirated and unaspirated sounds are weak; Bang 幫 and Pang 滂 are occasionally confused; and Fei 非 and Fu 敷 are merged. Voiced and voiceless initials are sometimes mixed, but full devoicing has not occurred. (2) In the coronal series, Duan Zu 端組 shows high internal interchange and Zhi Zu 知組 tends to mix with Zhang Zu 章組 and Zhuang Zu 莊組. (3) In the sibilant and affricate series, Jing 精 and Zhuang 莊 are merged; Chuan 船 and Shan 禪 also merge, while Cong 從 and Xie 邪 only occasionally alternate. (4) In the velar and laryngeal series, fully voiced Qun 羣 is close to voiceless initials, while Yun 云 and Yi 以 are closely related. Nasal and lateral initials maintain independence. The findings suggest that Yongle Nanzang 永乐南藏 is not a direct reprint of the Qishazang 磧砂藏, but rather a revised edition adapted to editorial or regional considerations. This study demonstrates the value of digital phonological methods in historical phonology and the significance of the Ming–Qing Chinese Buddhist canon. Full article

Recognising the Bangla alphabet remains a significant challenge within the fields of computational linguistics and artificial intelligence, primarily due to the script’s inherent structural complexity and wide variability in writing styles. The Bangla script is characterised by intricate ligatures, overlapping diacritics, and visually similar graphemes, all of which complicate automated recognition tasks. Despite ongoing advancements in deep learning (DL), machine learning (ML), and image processing (IP), accurately identifying Bangla characters continues to be a demanding and unresolved issue. A key limitation lies in the absence of robust detection frameworks capable of accommodating the script’s complex visual patterns and nuances. To address this gap, we propose an enhanced object detection model based on the YOLOv11 architecture, incorporating a ResNet50 backbone for improved feature extraction. The YOLOv11 framework is particularly effective in capturing discriminative features from input images, enabling real-time detection with high precision. This is especially beneficial in overcoming challenges such as character overlap and stylistic diversity, which often hinder conventional recognition techniques. Our approach was evaluated on a custom dataset comprising 50 primary Bangla characters (including vowels and consonants) along with 10 numerical digits. The proposed model achieved a recognition confidence of 99.9%, markedly outperforming existing methods in terms of accuracy and robustness. This work underscores the potential of single-shot detection models for the recognition of complex scripts such as Bangla. Beyond its technical contributions, the model has practical implications in areas including the digitisation of historical documents, the development of educational tools, and the advancement of inclusive multilingual technologies. By effectively addressing the unique challenges posed by the Bangla script, this research contributes meaningfully to both computational linguistics and the preservation of linguistic heritage. Full article

Background/Objectives: This study investigates the application of machine learning (ML) techniques in diagnosing speech sound disorders (SSDs) in Saudi Arabic-speaking children, with a specific focus on phonological biomarkers, particularly Infrequent Variance (InfrVar), to improve diagnostic accuracy. SSDs are a significant concern in pediatric speech pathology, affecting an estimated 10–15% of preschool-aged children worldwide. However, accurate diagnosis remains challenging, especially in linguistically diverse populations. Traditional diagnostic tools, such as the Percentage of Consonants Correct (PCC), often fail to capture subtle phonological variations. This study explores the potential of machine learning models to enhance diagnostic accuracy by incorporating culturally relevant phonological biomarkers like InfrVar, aiming to develop a more effective diagnostic approach for SSDs in Saudi Arabic-speaking children. Methods: Data from 235 Saudi Arabic-speaking children aged 2;6 to 5;11 years were analyzed using several machine learning models: Random Forest, Support Vector Machine (SVM), XGBoost, Logistic Regression, K-Nearest Neighbors, and Naïve Bayes. The dataset was used to classify speech patterns into four categories: Atypical, Typical Development (TD), Articulation, and Delay. Phonological features such as Phonological Variance (PhonVar), InfrVar, and Percentage of Consonants Correct (PCC) were used as key variables. SHapley Additive exPlanations (SHAP) analysis was employed to interpret the contributions of individual features to model predictions. Results: The XGBoost and Random Forest models demonstrated the highest performance, with an accuracy of 91.49% and an AUC of 99.14%. SHAP analysis revealed that articulation patterns and phonological patterns were the most influential features for distinguishing between Atypical and TD categories. The K-Means clustering approach identified four distinct subgroups based on speech development patterns: TD (46.61%), Articulation (25.42%), Atypical (18.64%), and Delay (9.32%). Conclusions: Machine learning models, particularly XGBoost and Random Forest, effectively classified speech development categories in Saudi Arabic-speaking children. This study highlights the importance of incorporating culturally specific phonological biomarkers like InfrVar and PhonVar to improve diagnostic precision for SSDs. These findings lay the groundwork for the development of AI-assisted diagnostic tools tailored to diverse linguistic contexts, enhancing early intervention strategies in pediatric speech pathology. Full article

This paper examines Gorgia Toscana (GT), a phenomenon of stop lenition observed in Tuscan varieties of Italian. Traditionally, this process has been understood to occur in post-vocalic positions, which, in the native lexicon, corresponds to onset position due to the absence of stops in syllable codas in Italian, apart from geminate consonants that straddle the coda and onset of adjacent syllables. However, stops in coda positions are found in both loanwords (e.g., admin, Batman) and bookwords (e.g., ritmo, tecnica). Drawing on original acoustic data collected from 42 native speakers of Florentine Italian, we investigated the realization of stops in such lexical items through allophonic classification and quantitative analysis. Our primary aim was to test the Onset Hypothesis, which posits that Gorgia exclusively affects stops in onset positions, implying that coda stops should not undergo lenition. Our findings support this hypothesis. We provide a phonological analysis within the frameworks of Strict CV and Coda Mirror, emphasizing the importance of syllable structure in understanding the manifestation of Gorgia Toscana, which we argue cannot be adequately captured solely by considering the linear order of segments. Full article

Despite being fundamental for speech processing, L2 perceptual training often lacks attention in L2 classrooms, especially among English as Foreign Language (EFL) learners navigating complex English phonology. The current study investigates the impact of the blended phonetic training program incorporating HVPT features on enhancing L2 perception and listening comprehension skills in Korean elementary EFL learners. Fifty-seven learners, aged 11 to 12 years, participated in a four-week intervention program. They were trained on 13 challenging consonant phonemes for Korean learners, using multimedia tools for practice. Pre- and posttests assessed L2 perception and listening comprehension. They are grouped into three proficiency levels based on listening comprehension tests. The results showed significant improvements in L2 perception (p = 0.01) with small and in listening comprehension (p < 0.001) with small-to-medium effects. The lower proficiency students demonstrated the largest gains. The correlation between L2 perception and listening comprehension was observed both in pre- (r = 0.427 **) and posttests (r = 0.479 ***). Findings underscore the importance of integrating explicit phonetic instruction with HVPT to enhance L2 listening skills among EFL learners. Full article

This article presents acoustic data on coarticulatory vowel nasalization from the productions of twelve L1 Korean speakers and of fourteen Korean learners of L2 English. The dataset includes eight monosyllabic target words embedded in eight carrier sentences, each repeated four times per speaker. Half of the words contain a nasal coda such as p*am in Korean and bomb in English and the other half a nasal onset such as mat in Korean and mob in English. These were produced under varied prosodic conditions, including three phrase positions and two focus conditions, enabling analysis of prosodic effects on vowel nasalization across languages along with individual speaker variation. The accompanying CSV files provide acoustic measurements such as nasal consonant duration, A1-P0, and normalized A1-P0 at multiple timepoints within the vowel. While theoretical implications have been discussed in two published studies, the full dataset is published here. By making these data publicly available, we aim to promote broad reuse and encourage further research at the intersection of prosody, phonetics, and second language acquisition—ultimately advancing our understanding of how phonetic patterns emerge, transfer, and vary across languages and learners. Full article

In this article, we analyse durational variation for inherently long consonants in Italian. Productions by 40 speakers of four regional varieties were elicited via a read-aloud task containing target words with inherently long consonants in the post-consonantal vs. intervocalic position. The analysis of acoustic durations revealed variation. Overall, we found that /ts/, /dz/ and /ʎ/ were considerably longer intervocalically than post-consonantally, although by smaller ratios than those reported in the literature for contrastive geminates; the effect was smaller for /ʃ/ and barely detectable for /ɲ/. We also detected a trend to lengthen /dz/ and /ʃ/ after a morphemic boundary. In terms of regional variation, north-eastern speakers were found to diverge from the others, with shorter durations and less consistent durational patterns. Additionally, we verified the existence of lengthening induced by double letters for /ts/ (vizi—vizzi) and /dz/ (Gaza—gazza), and only found it for /dz/, particularly for north-eastern speakers. We argue that this may originally have been an orthographic effect due to the acquisition of Italian at school via the written form by past generations, which has been lost for /ts/ but preserved for /dz/ under the influence of loanwords spelled with <z> and pronounced as short intervocalically. Full article

Investigating how facial movements can be used to characterize and quantify speech is important, in particular, to aid those suffering from motor control speech disorders. Here, we sought to investigate how facial action units (AUs), previously used to classify human expressions and emotion, could be used to quantify and understand unimpaired human speech. Fourteen (14) adult participants (30.1 ± 7.9 years old), fluent in English, with no speech impairments, were examined. Within each data collection session, 6 video trials per participant per phoneme were acquired (i.e., 102 trials total/phoneme). The participants were asked to vocalize the vowels /æ/, /ɛ/, /ɪ/, /ɒ/, and /ʊ/; the consonants /b/, /n/, /m/, /p/, /h/, /w/, and /d/; and the diphthongs /eI/, /ʌɪ/, /i/, /a:/, and /u:/. Through the use of Python Py-Feat, our analysis displayed the AU contributions for each phoneme. The important implication of our methodological findings is that AUs could be used to quantify speech in populations with no speech disability; this has the potential to be broadened toward providing feedback and characterization of speech changes and improvements in impaired populations. This would be of interest to persons with speech disorders, speech language pathologists, engineers, and physicians. Full article