Search results for: figures of speech

Authors: I. Wardana Ketut, I. Suparwa Nyoman

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This study investigated the form and characteristic of speech sound produced by three Balinese subjects who have recovered from aphasia as well as intervened their language impairment on side of linguistic and neuronal aspects of views. The failure of judging the speech sound was caused by impairment of motor cortex that indicated there were lesions in left hemispheric language zone. Sound articulation phenomena were in the forms of phonemes deletion, replacement or assimilation in individual words and meaning building for anomic aphasia. Therefore, the Balinese sound patterns were stimulated by showing pictures to the subjects and recorded to recognize what individual consonants or vowels they unclearly produced and to find out how the sound disorder occurred. The physiology of sound production by subject’s speech organs could not only show the accuracy of articulation but also any level of severity the lesion they suffered from. The subjects’ speech sounds were investigated, classified and analyzed to know how poor the lingual units were and observed to clarify weaknesses of sound characters occurred either for place or manner of articulation. Many fricative and stopped consonants were replaced by glottal or palatal sounds because the cranial nerve, such as facial, trigeminal, and hypoglossal underwent impairment after the stroke. The phonological intervention was applied through a technique called phonemic articulation drill and the examination was conducted to know any change has been obtained. The finding informed that some weak articulation turned into clearer sound and simple meaning of language has been conveyed. The hierarchy of functional parts of brain played important role of language formulation and processing. From this finding, it can be clearly emphasized that this study supports the role of right hemisphere in recovery from aphasia is associated with functional brain reorganization.

Keywords: aphasia, intervention, phonology, stroke

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Authors: Robyn White, Juan Bornman, Ensa Johnson

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People with disabilities are at a high risk of becoming victims of crime. Individuals with little or no functional speech (LNFS) face an even higher risk. One way of reducing the risk of remaining a victim of crime is to face the alleged perpetrator in court as a witness – therefore it is important for a person with LNFS who has been a victim of crime to have the required vocabulary to testify in court. The aim of this study was to identify and describe the core and fringe legal vocabulary required by illiterate victims of crime, who have little or no functional speech, to testify in court as witnesses. A mixed-method, the exploratory sequential design consisting of two distinct phases was used to address the aim of the research. The first phase was of a qualitative nature and included two different data sources, namely in-depth semi-structured interviews and focus group discussions. The overall aim of this phase was to identify and describe core and fringe legal vocabulary and to develop a measurement instrument based on these results. Results from Phase 1 were used in Phase 2, the quantitative phase, during which the measurement instrument (a custom-designed questionnaire) was socially validated. The results produced six distinct vocabulary categories that represent the legal core vocabulary and 99 words that represent the legal fringe vocabulary. The findings suggested that communication boards should be individualised to the individual and the specific crime. It is believed that the vocabulary lists developed in this study act as a valid and reliable springboard from which communication boards can be developed. Recommendations were therefore made to develop an Alternative and Augmentative Communication Resource Tool Kit to assist the legal justice system.

Keywords: augmentative and alternative communication, person with little or no functional speech, sexual crimes, testifying in court, victim of crime, witness competency

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Authors: Catherine Wright, Kate Luedke

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This paper questions whether or not individuals who had been exposed to narratives describing secure and insecure-avoidant attachment styles experienced temporary changes in their attachment style when compared to individuals who had been exposed to neutral narratives. The Attachment Style Questionnaire (or ASQ) developed by Feeney, Noller, and Hanrahan in 1994 was utilized to assess attachment style. Participants filled out a truncated version of the ASQ prior to reading the respective narratives assigned to their groups, and filled out the entirety of the ASQ after reading the narratives. Utilizing a one-way independent groups ANOVA, researchers found that the group which read the insecure-avoidant narrative experienced a statistically significant decrease in secure attachment, as did the group which read the secure narrative. The control group, however, experienced a statistically significant increase in secure attachment. Based on these findings, researchers concluded that narratives may have the ability to call attention to parental shortcomings that individuals have experienced in the forms of reminding individuals of positive experiences that they were not able to experience while spending time with their parental figures and calling attention to the shortcomings of said parental figures by reminding them of the negative experiences which they did have with them.

Keywords: attachment, insecure-avoidant, memory, secure

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Authors: Rudinë Fetahaj, Flaka Isufi, Kristina Hansson

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While evidence shows that in most European countries’ multilingualism is rising, unfortunately, the focus of Speech and Language Therapy (SLT) is still monolingualism. Furthermore, there is sparse information on how the needs of multilingual children with language disorders such as Developmental Language Disorder (DLD) are being met and which factors affect the intervention approach of SLTs when treating DLD. This study aims to examine the relationship and correlation between the number of languages SLTs speak, years of experience, and length of education with the advice they give to parents of multilingual children with DLD regarding which language to be spoken. This is a cross-sectional study where a survey was completed online by 2608 SLTs across Europe and data has been used from a 2017 COST-action project. IBM-SPSS-28 was used where descriptive analysis, correlation and Kruskal-Wallis test were performed.SLTs mainly advise the parents of multilingual children with DLD to speak their native language at home. Besides years of experience, language status and the level of education showed to have no association with the type of advice SLTs give. Results showed a non-significant moderate positive correlation between SLTs years of experience and their advice regarding the native language, whereas language status and length of education showed no correlation with the advice SLTs give to parents.

Keywords: quantitative study, developmental language disorders, multilingualism, speech and language therapy, children, European context

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Authors: Jui-Hsueh Hu

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This study investigated various models of refusal speech acts among three target groups: French learners of Mandarin Chinese (FM), Taiwanese native Mandarin speakers (TM), and native French speakers (NF). The refusal responses were analyzed in terms of their options, frequencies, and sequences and the contents of their semantic formulas. This study also examined differences in refusal strategies, as determined by social status and social distance, among the three groups. The difficulties of refusal speech acts encountered by FM were then generalized. The results indicated that Mandarin instructors of NF should focus on the different reasons for the pragmatic failure of French learners and should assist these learners in mastering refusal speech acts that rely on abundant cultural information. In this study, refusal policies were mainly classified according to the research of Beebe et al. (1990). Discourse completion questionnaires were collected from TM, FM, and NF, and their responses were compared to determine how refusal policies differed among the groups. This study not only emphasized the dissimilarities of refusal strategies between native Mandarin speakers and second-language Mandarin learners but also used NF as a control group. The results of this study demonstrated that regarding overall strategies, FM were biased toward NF in terms of strategy choice, order, and content, resulting in pragmatic transfer under the influence of social factors such as 'social status' and 'social distance,' strategy choices of FM were still closer to those of NF, and the phenomenon of pragmatic transfer of FM was revealed. Regarding the refusal difficulties among the three groups, the F-test in the analysis of variance revealed statistical significance was achieved for Role Playing Items 13 and 14 (P < 0.05). A difference was observed in the average number of refusal difficulties between the participants. However, after multiple comparisons, it was found that item 13 (unrecognized heterosexual junior colleague requesting contacts) was significantly more difficult for NF than for TM and FM; item 14 (contacts requested by an unrecognized classmate of the opposite sex) was significantly more difficult to refuse for NF than for TM. This study summarized the pragmatic language errors that most FM often perform, including the misuse or absence of modal words, hedging expressions, and empty words at the end of sentences, as the reasons for pragmatic failures. The common social pragmatic failures of FM include inaccurately applying the level of directness and formality.

Keywords: French Mandarin, interlanguage refusal, pragmatic transfer, speech acts

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Robert Long, Hiroaki Watanabe

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This longitudinal study examines the grammatical errors of Japanese university students’ dialogues with a native speaker over an academic year. The L2 interactions of 15 Japanese speakers were taken from the JUSFC2018 corpus (April/May 2018) and the JUSFC2019 corpus (January/February). The corpora were based on a self-introduction monologue and a three-question dialogue; however, this study examines the grammatical accuracy found in the dialogues. Research questions focused on a possible significant difference in grammatical accuracy from the first interview session in 2018 and the second one the following year, specifically regarding errors in clauses per 100 words, global errors and local errors, and with specific errors related to parts of speech. The investigation also focused on which forms showed the least improvement or had worsened? Descriptive statistics showed that error-free clauses/errors per 100 words decreased slightly while clauses with errors/100 words increased by one clause. Global errors showed a significant decline, while local errors increased from 97 to 158 errors. For errors related to parts of speech, a t-test confirmed there was a significant difference between the two speech corpora with more error frequency occurring in the 2019 corpus. This data highlights the difficulty in having students self-edit themselves.

Keywords: clause analysis, global vs. local errors, grammatical accuracy, L2 output, longitudinal study

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Glomus jugulare tumors arise within the jugular foramen and are commonly seen in females particularly on the left side. Surgical excision of the tumor may cause lower cranial nerve deficits. Cranial nerve involvement produces hoarseness of voice, slurred speech, and dysphagia along with other physical symptoms, thereby affecting the quality of life of individuals. Though oncological clearance is mainly emphasized on while treating these individuals, little importance is given to their communication, voice and swallowing problems, which play a crucial part in daily functioning. Objective: To examine the functions of voice, speech and swallowing outcomes of the subjects, following excision of glomus jugulare tumor. Methods: Two female subjects aged 56 and 62 years had come with a complaint of change in voice, inability to swallow and reduced clarity of speech following surgery for left glomus jugulare tumor were participants of the study. Their surgical information revealed multiple cranial nerve palsies involving the left facial, left superior and recurrent branches of the vagus nerve, left pharyngeal, left soft palate, left hypoglossal and vestibular nerves. Functional outcomes of voice, speech and swallowing were evaluated by perceptual and objective assessment procedures. Assessment included the examination of oral structures and functions, dysarthria by Frenchey dysarthria assessment, cranial nerve functions and swallowing functions. MDVP and Dr. Speech software were used to evaluate acoustic parameters of voice and quality of voice respectively. Results: The study revealed that both the subjects, subsequent to excision of glomus jugulare tumor, showed a varied picture of affected oral structure and functions, articulation, voice and swallowing functions. The cranial nerve assessment showed impairment of the vagus, hypoglossal, facial and glossopharyngeal nerves. Voice examination indicated vocal cord paralysis associated with breathy quality of voice, weak voluntary cough, reduced pitch and loudness range, and poor respiratory support. Perturbation parameters as jitter, shimmer were affected along with s/z ratio indicative of voice fold pathology. Reduced MPD(Maximum Phonation Duration) of vowels indicated that disturbed coordination between respiratory and laryngeal systems. Hypernasality was found to be a prominent feature which reduced speech intelligibility. Imprecise articulation was seen in both the subjects as the hypoglossal nerve was affected following surgery. Injury to vagus, hypoglossal, gloss pharyngeal and facial nerves disturbed the function of swallowing. All the phases of swallow were affected. Aspiration was observed before and during the swallow, confirming the oropharyngeal dysphagia. All the subsystems were affected as per Frenchey Dysarthria Assessment signifying the diagnosis of flaccid dysarthria. Conclusion: There is an observable communication and swallowing difficulty seen following excision of glomus jugulare tumor. Even with complete resection, extensive rehabilitation may be necessary due to significant lower cranial nerve dysfunction. The finding of the present study stresses the need for involvement of as speech and swallowing therapist for pre-operative counseling and assessment of functional outcomes.

Keywords: functional outcome, glomus jugulare tumor excision, multiple cranial nerve impairment, speech and swallowing

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

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Authors: Tamer Mesallam, Medhat Yousef, Ayna Almasaad

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BACKGROUND: Cochlear implantation (CI) in children with additional disabilities can be a fundamental and supportive intervention. Although, there may be some positive impacts of CI on children with multiple disabilities such as better outcomes of communication skills, development, and quality of life, the families of those children complain from the post-implant habilitation efforts that considered as a burden. OBJECTIVE: To investigate the outcomes of CI children with different co-disabilities through using the Meaningful Auditory Integration Scale (MAIS) and the Meaningful Use of Speech Scale (MUSS) as outcome measurement tools. METHODS: The study sample comprised 25 hearing-impaired children with co-disability who received cochlear implantation. Age and gender-matched control group of 25 cochlear-implanted children without any other disability has been also included. The participants' auditory skills and speech outcomes were assessed using MAIS and MUSS tests. RESULTS: There was a statistically significant difference in the different outcomes measure between the two groups. However, the outcomes of some multiple disabilities subgroups were comparable to the control group. Around 40% of the participants with co-disabilities experienced advancement in their methods of communication from behavior to oral mode. CONCLUSION: Cochlear-implanted children with multiple disabilities showed variable degrees of auditory and speech outcomes. The degree of benefits depends on the type of the co-disability. Long-term follow-up is recommended for those children.

Keywords: children with disabilities, Cochlear implants, hearing impairment, language development

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Marc Arthur Bien Aimé, Julio da Silveira Moreira

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This study examines the political speech in Haiti over the course of the decade 2011-2021, focusing on the speeches of the presidents Michel J. Martelly and Jovenel Moïse and their impacts on their awareness collective. In using a qualitative approach, we have analyzed the speech of the president pronounced in response to the political instability of countries, as well as interviews with a group of 20 Haitians living in Port- Au-Prince. Our results put in evidence their complex relationship between politics, awareness collective, and the influence of the powers imperialists. We show that the situation in Haiti's disastrous social and political situation is driven by personal political interests and the absence of a state political project. Moreover, the speeches of the president’s analysis are meaningless, transforming concepts such as social progress and justice in simple words. This political rhetoric contributes to the domination symbolic of the population of Haitian. This study is also linked to the theme “Constitutions, processes democratic and critical of the state in Latin America,” emphasizing the importance of analysis of political speech to understand the complexities of the democratic process and criticism of the State in their Latin American region. We suggest future research to deepen our understanding of these political dynamics and their impact on public policies and developments of the constitutions throughout Latin America.

Keywords: political discourse, conscience collective, inequality social, democratic processes, constitutions, Haiti

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Authors: M. Leonora D. Guerrero

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The study attempted to uncover the most and least frequent phonological variation evident in the speech patterns of grade 1 teachers in select public elementary schools in the Philippines. It also determined the lectal description of the participants based on Tayao’s consonant charts for American and Philippine English. Descriptive method was utilized. A total of 24 grade 1 teachers participated in the study. The instrument used was word list. Each column in the word list is represented by words with the target consonant phonemes: labiodental fricatives f/ and /v/ and lingua-alveolar fricative /z/. These phonemes were in the initial, medial, and final positions, respectively. Findings of the study revealed that the most frequent variation happened when the participants read words with /z/ in the final position while the least frequent variation happened when the participants read words with /z/ in the initial position. The study likewise proved that the grade 1 teachers exhibited the segmental features of both the mesolect and basilect. Based on these results, it is suggested that teachers of English in the Philippines must aspire to manifest the features of the mesolect, if not, the acrolect since it is expected of the academicians not to be displaying the phonological features of the acrolects since this variety is only used by the 'uneducated.' This is especially so with grade 1 teachers who are often mimicked by their students who classify their speech as the 'standard.'

Keywords: consonant phonemes, lectal description, Philippine English, phonological variation

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Dina Mahmoud Hammouri

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The study investigates the Jordanian EFL learners’ pragmatic competence through their production of the speech acts of responding to requests, making suggestions, making threats and expressing farewells. The sample of the study consists of 130 Jordanian EFL learners and native speakers. 2600 responses were collected through a Discourse Completion Test (DCT). The findings of the study revealed that the tested students showed similarities and differences in performing the strategies of four speech acts. Differences in the students’ performances led to pragmatic failure instances. The pragmatic failure committed by students refers to a lack of linguistic competence (i.e., pragmalinguistic failure), sociocultural differences and pragmatic transfer (i.e., sociopragmatic failure). EFL learners employed many mechanisms to maintain their communicative competence; the analysis of the test on speech acts showed learners’ tendency towards using particular strategies, resorting to modify strategies and relating them to their grammatical competence, prefabrication, performing long forms, buffing and transfer. The results were also suggestive of the learners’ lack of pragmalinguistic and sociopragmatic knowledge. The implications of this study are for language teachers to teach interlanguage pragmatics explicitly in EFL contexts to draw learners’ attention to both pragmalinguistic and sociopragmatic features, pay more attention to these areas and allocate more time and practice to solve learners’ problems in these areas. The implication of this study is also for pedagogical material designers to provide sufficient and well-organized pragmatic input.

Keywords: pragmatic failure, Jordanian EFL learner, sociopragmatic competence, pragmalinguistic competence

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Authors: Anochao Phetcharat

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This research aims to study problems of translation basic knowledge, particularly from English into Thai. The researcher used 38 2nd-year non-English speaking students of Suratthani Rajabhat University as samples. The samples were required to translate an A4-sized article from English into Thai assigned as a part of BEN0202 Translation for Business, a requirement subject for Business English Department, which was also taught by the researcher. After completion of the translation, numerous problems were found and the research grouped them into 4 major types. The normally occurred problems in English-Thai translation works are the lack of knowledge in terms of parts of speech, word-by-word translation employment, misspellings as well as the poor knowledge in English language structure. However, this research is currently under the process of data analysis and shall be completed by the beginning of August. The researcher, nevertheless, predicts that all the above-mentioned problems, will support the researcher’s hypothesizes, that are; 1) the lack of knowledge in terms of parts of speech causes the mistranslation problem; 2) employing word-by-word translation technique hugely results in the mistranslation problem; 3) misspellings yields the mistranslation problem; and 4) the poor knowledge in English language structure also brings about translation errors. The research also predicts that, of all the aforementioned problems, the following ones are found the most, respectively: the poor knowledge in English language structure, word-by-word translation employment, the lack of knowledge in terms of parts of speech, and misspellings.

Keywords: problem, student, Thai, translation

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

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With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Konysbek Aksaule

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The purpose of this work is to explore new and effective ways of teaching English to students who are studying a foreign language since the timeliness of the problem disclosed in this article is due to the high level of English proficiency that potential specialists must have due to high competition in the context of global globalization. The article presents an analysis of the feasibility and effectiveness of using an authentic feature film in teaching English to students. The methodological basis of the study includes an assessment of the level of students' proficiency in a foreign language, the stage of evaluating the film, and the method of selecting the film for certain categories of students. The study also contains a list of practical tasks that can be applied in the process of viewing and perception of an original feature film in a foreign language, and which are aimed at developing language skills such as speaking and listening. The results of this study proved that teaching English to students through watching an original film is one of the most effective methods because it improves speech perception, speech reproduction ability, and also expands the vocabulary of students and makes their speech fluent. In addition, learning English through watching foreign films has a huge impact on the cultural views and knowledge of students about the country of the language being studied and the world in general. Thus, this study demonstrates the high potential of using authentic feature film in English lessons for pedagogical science and methods of teaching English in general.

Keywords: university, education, students, foreign language, feature film

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: Lokman Gozcu, Sule Deniz Gozcu

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This study aims to analyze the skills of speaking in the acquisition of Turkish as a foreign language. One of the most important things for the individual who learns a foreign language is to be successful in the oral communication (speaking) skills and to interact in an understandable way. Speech skill requires much more time and effort than other language skills. In this direction, it is necessary to make an analysis of these oral communication skills, which is important in Turkish language acquisition as a foreign language and to draw out a road map according to the result. The aim of this study is to determine the competence and attitudes of speaking competence according to the individuals who learn Turkish as a foreign language and to be considered as speaking skill elements; Grammar, emphasis, intonation, body language, speed, ranking, accuracy, fluency, pronunciation, etc. and the results and suggestions based on these determinations. A mixed method has been chosen for data collection and analysis. A Likert scale (for competence and attitude) was applied to 190 individuals who were interviewed face-to-face (for speech skills) with a semi-structured interview form about 22 participants randomly selected. In addition, the observation form related to the 22 participants interviewed were completed by the researcher during the interview, and after the completion of the collection of all the voice recordings, analyses of voice recordings with the speech skills evaluation scale was made. The results of the research revealed that the speech skills of the individuals who learned Turkish as a foreign language have various perspectives. According to the results, the most inadequate aspects of the participants' ability to speak in Turkish include vocabulary, using humorous elements while speaking Turkish, being able to include items such as idioms and proverbs while speaking Turkish, Turkish fluency respectively. In addition, the participants were found not to feel comfortable while speaking Turkish, to feel ridiculous and to be nervous while speaking in formal settings. There are conclusions and suggestions for the situations that arise after the have been analyses made.

Keywords: learning Turkish as a foreign language, proficiency criteria, phonetic (modalities), speaking skills

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Authors: Akemi Nasu, Keiko Matsumoto

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Rehabilitation for cancer requires setting up individual goals for each patient and an approach that properly fits the stage of cancer when putting into practice. In order to cope with the daily changes in the patients' condition, the establishment of a good cooperative relationship between the nurses and the physiotherapists, occupational therapists, and speech-language-hearing therapists (therapists) becomes essential. This study will focus on the present situation of the cooperation between nurses and therapists, especially the speech-language-hearing therapists, and aim to elucidate what develops there. A semi-structured interview was conducted targeted at a physical therapist having practical experience in working in collaboration with nurses. The contents of the interview were transcribed and converted to data, and the data was encoded and categorized with sequentially increasing degrees of abstraction to conduct a qualitative explorative factor analysis of the data. When providing ethical explanations, particular care was taken to ensure that participants would not be subjected to any disadvantages as a result of participating in the study. In addition, they were also informed that their privacy would be ensured and that they have the right to decline to participate in the study. In addition, they were also informed that the results of the study would be announced publicly at an applicable nursing academic conference. This study has been approved following application to the ethical committee of the university with which the researchers are affiliated. The survey participant is a female speech-language-hearing therapist in her forties. As a result of the analysis, 6 categories were extracted consisting of 'measures to address appetite and aspiration pneumonia prevention', 'limitation of the care a therapist alone could provide', 'the all-inclusive patient- supportive care provided by nurses', 'expand the beneficial cooperation with nurses', 'providing education for nurses on the swallowing function utilizing videofluoroscopic examination of swallowing', 'enhancement of communication including conferences'. In order to improve the team performance, and for the teamwork competency necessary for the provision of safer care, mutual support is essential. As for the cooperation between nurses and therapists, this survey indicates that the maturing of the cooperation between professionals in order to improve nursing professionals' knowledge and enhance communication will lead to an improvement in the quality of the rehabilitation for cancer.

Keywords: cancer rehabilitation, nurses, speech-language-hearing therapists, interprofessional work

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Authors: Nami Takase

Abstract:

Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Premvadee Na Nakornpanom

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Language mixing in spontaneous speech has been widely discussed, but not in virtual situations; especially in context of the third language learning students. Thus, this study was an attempt to explore the characteristics of the mixing of Japanese, English and Thai in a mobile chat room by students with their background of Japanese, English, and Thai. The result found that Insertion of Thai and English content words was a very common linguistic phenomenon embedded in the utterances. As chatting is to be ‘relational’ or ‘interactional’, it affected the style of lexical choices to be speech-like, more personal and emotional-related. A Japanese sentence-final question particle“か”(ka) was added to the end of the sentence based on Thai grammar rule. Moreover, some unique characteristics were created. The non-verbal cues were represented in personal, Thai styles by inserting textual representations of images or feelings available on the websites into streams of conversations.

Keywords: code-mixing, Japanese, English, Thai, line chat

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Authors: Abdelghani May

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This paper reports on experimental investigations concerning the underlying reasons for the anisotropic behavior observed during the cyclic loading of AA2017 aluminum alloy. Initially, we quantified the evolution of fatigue damage resulting from controlled proportional cyclic loadings along the axial and shear directions. Our primary objective at this stage was to verify the anisotropic mechanical behavior recently observed. To accomplish this, we utilized various models of fatigue damage quantification and conducted a comparative study of the obtained results. Our analysis confirmed the anisotropic nature of the material under investigation. In the subsequent step, we performed microstructural investigations aimed at understanding the origins of the anisotropic mechanical behavior. To this end, we utilized scanning electron microscopy to examine the phases and precipitates in both the transversal and longitudinal sections. Our findings indicate that the structure and morphology of these entities are responsible for the anisotropic behavior observed in the aluminum alloy. Furthermore, results obtained from Kikuchi diagrams, pole figures, and inverse pole figures have corroborated these conclusions. These findings demonstrate significant differences in the crystallographic texture of the material.

Keywords: microstructural investigation, fatigue damage quantification, anisotropic behavior, AA2017 aluminum alloy, cyclic loading, crystallographic texture, scanning electron microscopy

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Mairo Musa Galadima, Phoebe Mshelia

Abstract:

In Nigeria, the national policy of education stipulates that the kindergarten primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5(five) selected secondary school in Bauchi. It was discover that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequate qualified teachers and relevant materials including text-books. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: kindergarten, stress, phonetic and intonation, Nigeria

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Authors: Hailang Yang

Abstract:

To ensure the confidentiality and integrity of speech signals in communication transmission, this paper proposes a voice signal encryption scheme based on chaotic theory. Firstly, the scheme utilizes chaotic mapping to generate a key stream and then employs the key stream to perform bitwise exclusive OR (XOR) operations for encrypting the speech signal. Additionally, the scheme utilizes a chaotic hash function to generate a Message Authentication Code (MAC), which is appended to the encrypted data to verify the integrity of the data. Subsequently, we analyze the security performance and encryption efficiency of the scheme, comparing and optimizing it against existing solutions. Finally, experimental results demonstrate that the proposed scheme can resist common attacks, achieving high-quality encryption and speed.

Keywords: chaotic theory, XOR encryption, chaotic hash function, Message Authentication Code (MAC)

Procedia PDF Downloads 29