Search results for: speech signal analysis

Authors: Aristi Alopoudi, Sofia Beloka, Vassiliki Pliogou

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Autism is a complex neuro-developmental disorder with a variety of difficulties in many aspects such as social interaction, communication skills and verbal communication (speech). The aim of this study was to examine the impact of therapeutic horseback riding in improving the verbal and communication skills of children diagnosed with autism during 16 sessions. The researcher examined whether the expression of speech, the use of vocabulary, semantics, pragmatics, echolalia and communication skills were influenced by the therapeutic horseback riding when we increase the frequency of the sessions. The researcher observed two subjects of primary-school aged, in a two case observation design, with autism during 16 therapeutic horseback riding sessions (one riding session per week). Compared to baseline, at the end of the 16th therapeutic session, therapeutic horseback riding increased both verbal skills such as vocabulary, semantics, pragmatics, formation of sentences and communication skills such as eye contact, greeting, participation in dialogue and spontaneous speech. It was noticeable that echolalia remained stable. Increased frequency of therapeutic horseback riding was beneficial for significant improvement in verbal and communication skills. More specifically, from the first to the last riding session there was a great increase of vocabulary, semantics, and formation of sentences. Pragmatics reached a lower level than semantics but the same as the right usage of the first person (for example, I make a hug) and echolalia used for that. A great increase of spontaneous speech was noticed. The eye contact was presented in a lower level, and there was a slow but important raise at the greeting as well as the participation in dialogue. Last but not least; this is a first study conducted in therapeutic horseback riding studying the verbal communication and communication skills in autistic children. According to the references, therapeutic horseback riding is a therapy with a variety of benefits, thus; this research made clear that in the benefits of this therapy there should be included the improvement of verbal speech and communication.

Keywords: Autism, communication skills, speech, therapeutic horseback riding

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Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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Authors: M. Lim Haslip

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This quantitative study explores the correlation between child gender and father-child interactions. The author analyzes data from videotaped interactions between African-American fathers and their boy or girl toddler to explain how African-American fathers and toddlers interact with each other and whether these interactions differ by child gender. The purpose of this study is to investigate the research question: 'How, if at all, do fathers’ speech and gestures differ when interacting with their two-year-old sons versus daughters during free play?' The objectives of this study are to describe how child gender impacts African-American fathers’ verbal communication, examine how fathers gesture and speak to their toddler by gender, and to guide interventions for low-income African-American families and their children in early language development. This study involves a sample of 41 low-income African-American fathers and their 24-month-old toddlers. The videotape data will be used to observe 10-minute father-child interactions during free play. This study uses the already transcribed and coded data provided by Dr. Meredith Rowe, who did her study on the impact of African-American fathers’ verbal input on their children’s language development. The Child Language Data Exchange System (CHILDES program), created to study conversational interactions, was used for transcription and coding of the videotape data. The findings focus on the quantity of speech, diversity of speech, complexity of speech, and the quantity of gesture to inform the vocabulary usage, number of spoken words, length of speech, and the number of object pointings observed during father-toddler interactions in a free play setting. This study will help intervention and prevention scientists understand early language development in the African-American population. It will contribute to knowledge of the role of African-American fathers’ interactions on their children’s language development. It will guide interventions for the early language development of African-American children.

Keywords: parental engagement, early language development, African-American families, quantity of speech, diversity of speech, complexity of speech and the quantity of gesture

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Authors: Anja Kurz, Marc Flynn, Tobias Good, Marco Caversaccio, Martin Kompis

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Bone Anchored Hearing Implants (BAHI) are routinely used in patients with conductive or mixed hearing loss, e.g. if conventional air conduction hearing aids cannot be used. New sound processors and new fitting software now allow the adjustment of parameters such as loudness compression ratios or maximum power output separately. Today it is unclear, how the choice of these parameters influences aided speech understanding in BAHI users. In this prospective experimental study, the effect of varying the compression ratio and lowering the maximum power output in a BAHI were investigated. Twelve experienced adult subjects with a mixed hearing loss participated in this study. Four different compression ratios (1.0; 1.3; 1.6; 2.0) were tested along with two different maximum power output settings, resulting in a total of eight different programs. Each participant tested each program during two weeks. A blinded Latin square design was used to minimize bias. For each of the eight programs, speech understanding in quiet and in noise was assessed. For speech in quiet, the Freiburg number test and the Freiburg monosyllabic word test at 50, 65, and 80 dB SPL were used. For speech in noise, the Oldenburg sentence test was administered. Speech understanding in quiet and in noise was improved significantly in the aided condition in any program, when compared to the unaided condition. However, no significant differences were found between any of the eight programs. In contrast, on a subjective level there was a significant preference for medium compression ratios of 1.3 to 1.6 and higher maximum power output.

Keywords: Bone Anchored Hearing Implant, baha, compression, maximum power output, speech understanding

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Authors: Helmi Baazaoui, Mounir Zrigui

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This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.

Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

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Authors: Sadeq Al Yaari, Fayza Al Hammadi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Salah Al Yami

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Background: When we further take Arabic grammatical issues into account in accordance with applied linguistic investigations on Arabic as Second Language (ASL) learners, a fundamental issue arises at this point as to the production of speech in Arabic: Oral grammatical errors committed by ASL learners. Aims: Using manual rating as well as computational analytic methodology to test a corpus of recorded speech by Second Language (ASL) learners of Arabic, this study aims to find the areas of difficulties in learning Arabic grammar. More specifically, it examines how and why ASL learners make grammatical errors in their oral speech. Methods: Tape recordings of four (4) Arabic as Second Language (ASL) learners who ranged in age from 23 to 30 were naturally collected. All participants have completed an intensive Arabic program (two years) and 20 minute-speech was recorded for each participant. Having the collected corpus, the next procedure was to rate them against Arabic standard grammar. The rating includes four processes: Description, analysis and assessment. Conclusions: Outcomes made from the issues addressed in this paper can be summarized in the fact that ASL learners face many grammatical difficulties when studying Arabic word order, tenses and aspects, function words, subject-verb agreement, verb form, active-passive voice, global and local errors, processes-based errors including addition, omission, substitution or a combination of any of them.

Keywords: grammar, error, oral, Arabic, second language, learner, applied linguistics.

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: N. Kh. Gomidze, I. N. Jabnidze, K. A. Makharadze

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The influence of inhomogeneities of plasma and statistical characteristics on the propagation of signal is very actual in wireless communication systems. While propagating in the media, the deformation and evaluation of the signal in time and space take place and on the receiver we get a deformed signal. The present article is dedicated to studying the space-time evolution of rectangular, sinusoidal, exponential and bi-exponential impulses via numerical experiment in the collisional, cold plasma. The presented method is not based on the Fourier-presentation of the signal. Analytically, we have received the general image depicting the space-time evolution of the radio impulse amplitude that gives an opportunity to analyze the concrete results in the case of primary impulse.

Keywords: collisional, cold plasma, rectangular pulse signal, impulse envelope

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Authors: Mai Yen Nhi Doan, Viet Le, Chamindika Weerakoon

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Social enterprises have emerged as sustainable organisations that deliver social achievement along with long-term financial advancement. However, recorded financial barriers have urged social enterprises to divert to other financing methods due to the misaligned ideology with traditional financing capitalists, in which crowdfunding can be a promising alternative. Previous studies in crowdfunding have inadequately addressed crowdfunding for social enterprises, with conflicting results due to the unsuitable analysis of signals in isolation rather than in combinations, using the data from platforms that do not support social enterprises. Extending the signalling theory, this study suggests that crowdfunding success results from the collaboration between costly and costless signals. The proposed conceptual framework enlightens the interaction between costly signals as “organisational information”, “social entrepreneur’s credibility,” and “third-party endorsement” and costless signals as various sub-signals under the “campaign preparedness” signal to achieve crowdfunding success. Using Qualitative Comparative Analysis, this study examined 45 crowdfunding campaigns run by Australian social enterprises on StartSomeGood and Chuffed. The analysis found that different combinations of costly and costless signals can lead to crowdfunding success, allowing social enterprises to adopt suitable combinations of signals to their context. Costless signal – campaign preparedness is fundamental for success, though different costless sub-signals under campaign preparedness can interact with different costly signals for the desired outcome. Third-party endorsement signal was found to be the necessary signal for crowdfunding success for Australian social enterprises.

Keywords: crowdfunding, qualitative comparative analysis (QCA), signalling theory, social enterprises

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Authors: Savita, Anurag Sharma, Harsukhpreet Singh

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Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

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Authors: Arianna Vedaschi

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This paper addresses the relationship between freedom of expression, national security and radicalization. Is it still possible to talk about a balance between the first two elements? Or, due to the intrusion of the third, is it more appropriate to consider freedom of expression as “permanently disfigured” by securitarian concerns? In this study, both the legislative and the judicial level are taken into account and the comparative method is employed in order to provide the reader with a complete framework of relevant issues and a workable set of solutions. The analysis moves from the finding according to which the tension between free speech and national security has become a major issue in democratic countries, whose very essence is continuously endangered by the ever-changing and multi-faceted threat of international terrorism. In particular, a change in terrorist groups’ recruiting pattern, attracting more and more people by way of a cutting-edge communicative strategy, often employing sophisticated technology as a radicalization tool, has called on law-makers to modify their approach to dangerous speech. While traditional constitutional and criminal law used to punish speech only if it explicitly and directly incited the commission of a criminal action (“cause-effect” model), so-called glorification offences – punishing mere ideological support for terrorism, often on the web – are becoming commonplace in the comparative scenario. Although this is direct, and even somehow understandable, consequence of the impending terrorist menace, this research shows many problematic issues connected to such a preventive approach. First, from a predominantly theoretical point of view, this trend negatively impacts on the already blurred line between permissible and prohibited speech. Second, from a pragmatic point of view, such legislative tools are not always suitable to keep up with ongoing developments of both terrorist groups and their use of technology. In other words, there is a risk that such measures become outdated even before their application. Indeed, it seems hard to still talk about a proper balance: what was previously clearly perceived as a balancing of values (freedom of speech v. public security) has turned, in many cases, into a hierarchy with security at its apex. In light of these findings, this paper concludes that such a complex issue would perhaps be better dealt with through a combination of policies: not only criminalizing ‘terrorist speech,’ which should be relegated to a last resort tool, but acting at an even earlier stage, i.e., trying to prevent dangerous speech itself. This might be done by promoting social cohesion and the inclusion of minorities, so as to reduce the probability of people considering terrorist groups as a “viable option” to deal with the lack of identification within their social contexts.

Keywords: radicalization, free speech, international terrorism, national security

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Pushpavathi M., Kavya V., Akshatha V.

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Introduction: Cleft lip and palate (CLP) is a congenital condition which hinders effectual communication due to associated speech and language difficulties. Expressive language delay (ELD) is a feature seen in this population which is influenced by factors such as type and severity of CLP, age at surgical and linguistic intervention and also the type and intensity of speech and language therapy (SLT). Since CLP is the most common congenital abnormality seen in Indian children, early intervention is a necessity which plays a critical role in enhancing their speech and language skills. The interaction between the timing of intervention and factors which contribute to effective intervention by caregivers is an area which needs to be explored. Objectives: The present study attempts to determine the effect of timing of intervention on the contributing maternal factors for effective linguistic intervention in toddlers with repaired CLP with respect to the awareness, home training patterns, speech and non-speech behaviors of the mothers. Participants: Thirty six toddlers in the age range of 1 to 4 years diagnosed as ELD secondary to repaired CLP, along with their mothers served as participants. Group I (Early Intervention Group, EIG) included 19 mother-child pairs who came to seek SLT soon after corrective surgery and group II (Delayed Intervention Group, DIG) included 16 mother-child pairs who received SLT after the age of 3 years. Further, the groups were divided into group A, and group B. Group ‘A’ received SLT for 60 sessions by Speech Language Pathologist (SLP), while Group B received SLT for 30 sessions by SLP and 30 sessions only by mother without supervision of SLP. Method: The mothers were enrolled for the Early Language Intervention Program and following this, their awareness about CLP was assessed through the Parental awareness questionnaire. The quality of home training was assessed through Mohite’s Inventory. Subsequently, the speech and non-speech behaviors of the mothers were assessed using a Mother’s behavioral checklist. Detailed counseling and orientation was done to the mothers, and SLT was initiated for toddlers. After 60 sessions of intensive SLT, the questionnaire and checklists were re-administered to find out the changes in scores between the pre- and posttest measurements. Results: The scores obtained under different domains in the awareness questionnaire, Mohite’s inventory and Mothers behavior checklist were tabulated and subjected to statistical analysis. Since the data did not follow normal distribution (i.e. p > 0.05), Mann-Whitney U test was conducted which revealed that there was no significant difference between groups I and II as well as groups A and B. Further, Wilcoxon Signed Rank test revealed that mothers had better awareness regarding issues related to CLP and improved home-training abilities post-orientation (p ≤ 0.05). A statistically significant difference was also noted for speech and non-speech behaviors of the mothers (p ≤ 0.05). Conclusions: Extensive orientation and counseling helped mothers of both EI and DI groups to improve their knowledge about CLP. Intensive SLT using focused stimulation and a parent-implemented approach enabled them to carry out the intervention in an effectual manner.

Keywords: awareness, cleft lip and palate, early language intervention program, home training, orientation, timing of intervention

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Authors: Anitha Naittee Abraham, N. Sreedevi

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Individuals with Down syndrome (DS) have relatively better expressive language compared to other individuals with intellectual disabilities. Reduced speech intelligibility is one of the major concerns of this group of individuals due to their anatomical and physiological differences. The study investigated the vowel articulation of Malayalam speaking children with DS in the age range of 5-10 years. The vowel production of 10 children with DS was compared with typically developing children in the same age range. Vowels were extracted from 3 words with the corner vowels /a/, /i/ and /u/ in the word-initial position, using Praat (version 5.3.23) software. Acoustic analysis was based on vowel space area (VSA), Formant centralization ration (FCR) and F2i/F2u. The findings revealed increased formant values for the control group except for F2a and F2u. Also, the experimental group had higher FCR, lower VSA, and F2i/F2u values suggestive of imprecise vowel articulation due to restricted tongue movements. The results of the independent t-test revealed a significant difference in F1a, F2i, F2u, VSA, FCR and F2i/F2u values between the experimental and control group. These findings support the fact that children with DS have imprecise vowel articulation that interferes with the overall speech intelligibility. Hence it is essential to target the oromotor skills to enhance the speech intelligibility which in turn benefit in the social and vocational domains of these individuals.

Keywords: Down syndrome, FCR, vowel articulation, vowel space

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Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

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In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

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Authors: Nurvita Wijayanti

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The movie titled The King’s Speech is based on a true story telling an English king suffers from stuttering and how he gets the treatment from the therapist, so that he can reduce the high frequency on stuttering. The treatment uses the unique approach implying the linguistic principles. This study shows how the language works significantly in order to treat the stuttering sufferer using psychological approach. Therefore, the linguistic study is done to analyze the treatment activity. Halliday’s Systemic Functional Grammar is used as the main approach in this study along with qualitative descriptive method. The study finds that the therapist though using the orthodox approach applies the psycholinguistic method to overcome the king’s stuttering.

Keywords: psycholinguistics, stuttering, systemic functional grammar, treatment

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Authors: Wahiba Mohguen, Raïs El’hadi Bekka

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This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: customized thresholding, ECG signal, EMD, hard thresholding, soft-thresholding

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Authors: Ahmed Elgadri

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In the last thirty years, studies on cross-cultural pragmatics in general and apology strategies in specific have focused on western and East-Asian societies. A small volume of research has been conducted in investigating speech acts production by Arabic dialect speakers. Therefore, this study investigated the apology strategies used by Libyan Arabic speakers using an online Discourse Completion Task (DCT) questionnaire. The DCT consisted of six situations covering different social contexts. The survey was written in Libyan Arabic dialect to help generate vernacular speech as much as possible. The participants were 25 Libyan nationals, 12 females, and 13 males. Also, to get a deeper understanding of the motivation behind the use of certain strategies, the researcher interviewed four participants using the Libyan Arabic dialect as well. The results revealed a high use of IFID, offer of repair, and explanation. Although this might support the universality claim of speech acts strategies, it was clear that cultural norms and religion determined the choice of apology strategies significantly. This led to the discovery of new culture-specific strategies, as outlined later in this paper. This study gives an insight into politeness strategies in Libyan society, and it is hoped to contribute to the field of cross-cultural pragmatics.

Keywords: apologies, cross-cultural pragmatics, language and culture, Libyan Arabic, politeness, pragmatics, socio-pragmatics, speech acts

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Authors: Siliang Luan

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In this paper, an integrated-decentralized bi-level optimization framework is developed to coordinate intersection signal operations and vehicle driving behavior at an isolated signalized intersection in a mixed traffic environment. The framework takes advantage of both signal control and conflict elimination by incorporating an integrated level and a decentralized level. Two distinct signal control methods are introduced: the classical green phase control strategy and the white phase control strategy. The latter allows certain vehicles to pass through the intersection during a red phase, thereby reducing idle time. Besides, various vehicle trajectory optimization strategies are tailored to different vehicle-following types, leveraging the capabilities of CAV technology. Enhanced microscopic behavior control strategies, such as car-following and lane-changing controls, are also developed for CAVs to improve their performance in mixed traffic. These strategies are integrated into the proposed framework. The effectiveness of the framework is validated through numerical experiments and sensitivity analysis, demonstrating its advantages in terms of traffic effectiveness, stability, and energy economy.

Keywords: traffic signal optimization, connected and automated vehicles, vehicle microscopic control, traffic control and information technology

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Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

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Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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Authors: Muhammad Fairul Azreen Mohd Zahid

Abstract:

Speech, text, and movement intensify aspects of creating choreography by connecting with emotional entanglements, tradition, literature, and other texts. This research focuses on the practice as research that will prioritise the choreography process as an inquiry approach. With the driven context, the study intervenes in critical conjunctions of choreographic theory, bringing together new reflections on the moving body, spaces of action, as well as intertextuality between text and movements in making choreography. Throughout the process, the researcher will introduce the level of deliberation from speech through movements and text to express emotion within a narrative context of an “illocutionary act.” This practice as research will produce a different meaning from the “utterance text” to “utterance movements” in the perspective of speech acts theory by J.L Austin based on fragmented text from “pidato adat” which has been used as opening speech in Randai. Looking at the theory of deconstruction by Jacque Derrida also will give a different meaning from the text. Nevertheless, the process of creating the choreography will also help to lay the basic normative structure implicit in “constative” (statement text/movement) and “performative” (command text/movement). Through this process, the researcher will also look at several methods of using text from two works by Joseph Gonzales, “Becoming King-The Pakyung Revisited” and Crystal Pite's “The Statement,” as references to produce different methods in making choreography. The perspective from the semiotic foundation will support how occurrences within dance discourses as texts through a semiotic lens. The method used in this research is qualitative, which includes an interview and simulation of the concept to get an outcome.

Keywords: intertextuality, choreography, speech act, performative, deconstruction

Procedia PDF Downloads 99

Authors: Yusra Ibrahim

Abstract:

This study explores the online discourse of justice-involved youth on Reddit, focusing on how anonymity and asynchronicity influence their ability to share and reflect on their incarceration experiences within the "Ask Me Anything" (AMA) community. The study utilizes a quantitative analysis of speech acts to examine the varied communication patterns exhibited by youths and commenters across two AMA threads. The results indicate that, although Reddit is not specifically designed for formerly incarcerated youths, its features provide a supportive environment for them to share their incarceration experiences with non-incarcerated individuals. The level of empathy and support from the audience varies based on the audience’s perspectives on incarceration and related traumatic experiences. Additionally, the study identifies a reciprocal relationship where youths benefit from community support while offering insights into the juvenile justice system and helping the audience understand the experience of incarceration. The study also reveals cultural shocks in physical and digital environments that youth experience after release and when using social media platforms and the internet. The study has implications for juvenile justice personnel, policymakers, and researchers in the juvenile justice system.

Keywords: juvenile justice, online discourse, reddit AMA, anonymity, speech acts taxonomy, reintegration, online community support

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Authors: Thapasya J., Rajesh Kumar

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Language plays complex roles in society. The previous studies on language and society explain their interconnected, complementary and complex interactions and, those studies were primarily focused on the variations in the language. Variation being the fundamental nature of languages, the question of personal and social identity navigated through language variation and established that there is an interconnection between language variation and identity. This paper analyses the sociolinguistic variation in language at the lexical level and how the lexical choice of the speaker(s) affects in shaping their identity. It obtains primary data from the lexicon of the Mappila dialect of Malayalam spoken by the members of Mappila (Muslim) community of Kerala. The variation in the lexical choice is analysed by collecting data from the speech samples of 15 minutes from four different age groups of Mappila dialect speakers. Various contexts were analysed and the frequency of borrowed words in each instance is calculated to reach a conclusion on how the variation is happening in the speech community. The paper shows how the lexical choice of the speakers could be socially motivated and involve in shaping and changing identities. Lexical items or vocabulary clearly signal the group identity and personal identity. Mappila dialect of Malayalam was rich in frequent use of borrowed words from Arabic, Persian and Urdu. There was a deliberate attempt to show their identity as a Mappila community member, which was derived from the socio-political situation during those days. This made a clear variation between the Mappila dialect and other dialects of Malayalam at the surface level, which was motivated to create and establish the identity of a person as the member of Mappila community. Historically, these kinds of linguistic variation were highly motivated because of the socio-political factors and, intertwined with the historical facts about the origin and spread of Islamism in the region; people from the Mappila community highly motivated to project their identity as a Mappila because of the social insecurities they had to face before accepting that religion. Thus the deliberate inclusion of Arabic, Persian and Urdu words in their speech helped in showing their identity. However, the socio-political situations and factors at the origin of Mappila community have been changed over a period of time. The social motivation for indicating their identity as a Mappila no longer exist and thus the frequency of borrowed words from Arabic, Persian and Urdu have been reduced from their speech. Apart from the religious terms, the borrowed words from these languages are very few at present. The analysis is carried out by the changes in the language of the people according to their age and found to have significant variations between generations and literacy plays a major role in this variation process. The need of projecting a specific identity of an individual would vary according to the change in the socio-political scenario and a variation in language can shape the identity in order to go with the varying socio-political situation in any language.

Keywords: borrowings, dialect, identity, lexical choice, literacy, variation

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Authors: Faiza Hussain, Usman Qamar

Abstract:

Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

Procedia PDF Downloads 308

Authors: Saurabh Farkya, Govinda Surampudi

Abstract:

Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

Procedia PDF Downloads 500

Authors: Attiq Ur Rahman Dogar, Sohaib Ishaq

Abstract:

Pakistan had experienced rapid motorization in the last decade. Due to the soft leasing schemes of banks and increase in average household income, even the middle class can now afford cars. The public transit system is inadequate and sparse. Due to these reasons, traffic demand on urban arterials has increased manifold. Poor urban transit planning and aging transportation systems have resulted in traffic congestion. The focus of this study is to improve traffic flow on a section of N-5 passing through the Rawalpindi downtown. Present efforts aim to carry out the analysis of traffic conditions on this section and to investigate the impact of traffic signal co-ordination on travel time. In addition to signal co-ordination, we also examined the effect of different infrastructure improvements on the travel time. After the economic analysis of alternatives and discussions, the improvement plan for Rawalpindi downtown urban arterial section is proposed for implementation.

Keywords: signal coordination, infrastructure intervention, infrastructure improvement, cycle length, fuel consumption cost, travel time cost, economic analysis, travel time, Rawalpindi, Pakistan, traffic signals

Procedia PDF Downloads 317