Search results for: speech rhythm

Authors: Muhammad Fairul Azreen Mohd Zahid

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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

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Authors: Hajer Rahali, Zied Hajaiej, Noureddine Ellouze

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The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.

Keywords: auditory filter, impulsive noise, MFCC, prosodic features, RASTA filter

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Authors: Djendi Mohmaed

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In this paper, we propose a dual adaptive algorithm, which is based on the combination between the forward blind source separation (FBSS) structure and the affine projection algorithm (APA). This proposed algorithm combines the advantages of the source separation properties of the FBSS structure and the fast convergence characteristics of the APA algorithm. The proposed algorithm needs two noisy observations to provide an enhanced speech signal. This process is done in a blind manner without the need for ant priori information about the source signals. The proposed dual forward blind source separation affine projection algorithm is denoted (DFAPA) and used for the first time in an airplane cockpit context to enhance the communication from- and to- the airplane. Intensive experiments were carried out in this sense to evaluate the performance of the proposed DFAPA algorithm.

Keywords: adaptive algorithm, speech enhancement, system mismatch, SNR

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Authors: Faiza Hussain, Usman Qamar

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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

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Authors: K. Shyamnath, K. Suresh Kutty

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The purpose of the study was to find out the effect of three resistance training methods on performance-related variables of powerlifters. A total of forty male students (N=40) who had participated in Kannur University powerlifting championship were selected as subjects. The age group of the subjects ranged from 18 years old to 25 years old. The selected subjects were equally divided into four groups (n=10) of three experimental groups and a control group. The experimental Group I underwent traditional resistance training (TRTG), Group II underwent combined traditional resistance training and plyometrics (TRTPG), and Group III underwent combined traditional resistance training and resistance training with high rhythm (TRTHRG). Group IV acted as the control group (CG) receiving no training during the experimental period. The duration of the experimental period was sixteen weeks, five days per week. Powerlifting performance was assessed by the 1RM test in the squat, bench press and deadlift. Performance-related variables assessed were chest girth, arm girth, forearm girth, thigh girth, and calf girth. Pre-test and post-test were conducted a day before and two days after the experimental period on all groups. Analysis of covariance (ANCOVA) was applied to analyze the significant difference. The 0.05 level of confidence was fixed as the level of significance to test the F ratio obtained by the analysis of covariance. The result indicates that there is a significant effect of all the selected resistance training methods on the performance and selected performance-related variables of powerlifters. Combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm proved better than the traditional resistance training in improving performance and selected performance-related variables of powerlifters. There was no significant difference between combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm in improving performance and selected performance-related variables of powerlifters.

Keywords: girth, plyometrics, powerlifting, resistance training

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Authors: Saurabh Farkya, Govinda Surampudi

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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)

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

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Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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Authors: Nataliya L. Ogurechnikova

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The paper aims to clarify the function of articles in the English speech and specify their place and role in the English language, taking into account the use of articles for delimitation of speech. A focus of the paper is the use of the definite and the indefinite articles with different types of noun phrases which comprise either one noun with or without attributes, such as the King, the Queen, the Lion, the Unicorn, a dimple, a smile, a new language, an unknown dialect, or several nouns with or without attributes, such as the King and Queen of Hearts, the Lion and Unicorn, a dimple or smile, a completely isolated language or dialect. It is stated that the function of delimitation is related to perception: the number of speech units in a text correlates with the way the speaker perceives and segments the denotation. The two following combinations of words the house and garden and the house and the garden contain different numbers of speech units, one and two respectively, and reveal two different perception modes which correspond to the use of the definite article in the examples given. Thus, the function of delimitation is twofold, it is related to perception and cognition, on the one hand, and, on the other hand, to grammar, if the subject of grammar is the structure of speech. Analysis of speech units in the paper is not limited by noun phrases and is amplified by discussion of peripheral phenomena which are nevertheless important because they enable to qualify articles as a syntactic phenomenon whereas they are not infrequently described in terms of noun morphology. With this regard attention is given to the history of linguistic studies, specifically to the description of English articles by Niels Haislund, a disciple of Otto Jespersen. A discrepancy is noted between the initial plan of Jespersen who intended to describe articles as a syntactic phenomenon in ‘A Modern English Grammar on Historical Principles’ and the interpretation of articles in terms of noun morphology, finally given by Haislund. Another issue of the paper is correlation between description and denotation, being a traditional aspect of linguistic studies focused on articles. An overview of relevant studies, given in the paper, goes back to the works of G. Frege, which gave rise to a series of scientific works where the meaning of articles was described within the scope of logical semantics. Correlation between denotation and description is treated in the paper as the meaning of article, i.e. a component in its semantic structure, which differs from the function of delimitation and is similar to the meaning of other quantifiers. The paper further explains why the relation between description and denotation, i.e. the meaning of English article, is irrelevant for noun morphology and has nothing to do with nominal categories of the English language.

Keywords: delimitation of speech, denotation, description, perception, speech units, syntax

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Authors: Ramesh K. Sunkaria, Puneeta Marwaha

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Nonlinear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy Normal Sinus Rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy

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Authors: Anindita Banik, Anjali Kant, Aninda Duti Banik, Arun Banik

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Speech is a complex, dynamic unique motor activity through which we express thoughts and emotions and respond to and control our environment. The aim was based to compare select Motor Speech parameters and their sub parameters across typical Marathi speaking adults and children. The subjects included a total of 300 divided into Group I, II, III including males and females. Subjects included were reported of no significant medical history and had a rating of 0-1 on GRBAS scale. The recordings were obtained utilizing three stimuli for the acoustic analysis of Diadochokinetic rate (DDK), Second Formant Transition, Voice and Tremor and its sub parameters. And these aforementioned parameters were acoustically analyzed in Motor Speech Profile software in VisiPitch IV. The statistical analyses were done by applying descriptive statistics and Two- Way ANOVA.The results obtained showed statistically significant difference across age groups and gender for the aforementioned parameters and its sub parameters.In DDK, for avp (ms) there was a significant difference only across age groups. However, for avr (/s) there was a significant difference across age groups and gender. It was observed that there was an increase in rate with an increase in age groups. The second formant transition sub parameter F2 magn (Hz) also showed a statistically significant difference across both age groups and gender. There was an increase in mean value with an increase in age. Females had a higher mean when compared to males. For F2 rate (/s) a statistically significant difference was observed across age groups. There was an increase in mean value with increase in age. It was observed for Voice and Tremor MFTR (%) that a statistically significant difference was present across age groups and gender. Also for RATR (Hz) there was statistically significant difference across both age groups and gender. In other words, the values of MFTR and RATR increased with an increase in age. Thus, this study highlights the variation of the motor speech parameters amongst the typical population which would be beneficial for comparison with the individuals with motor speech disorders for assessment and management.

Keywords: adult, children, diadochokinetic rate, second formant transition, tremor, voice

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

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Authors: Olga A. Gnatyuk

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The article is devoted to the phenomenon of interference that occurs in the case of the Russian-Spanish language contact. The questions of the definition of the term and levels, as well as prerequisites of interference occurrence, are considered. Interference, which is an essential part of bilingualism, may become apparent at different linguistic levels. Interference is especially evident in oral speech. The article reviews some examples of grammatical interference in Russian-Spanish bilingualism of Russian immigrants living in Spain. According to the results of the research, some cases of mother-tongue interference in Russian-Speaking Spanish language learners’ speech were revealed. Special attention is paid to such key spheres of grammatical interference as articles, personal pronouns, gender, and number of nouns. In the research, the drop of a link-verb, as well as its usage in some incorrect form, are observed in Russian immigrants’ speech. Conclusions are drawn that in the Spanish language, interference errors appear because of a consequence of both the absence in the Russian language of certain phenomena and categories of the Spanish language and the discrepancy of the linguistic systems of the two languages.

Keywords: bilingualism, interference, grammatical interference, Russian language, Spanish language

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Authors: Marlyn Mathew

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Communication is the key factor in any vocational /job set-up. However many persons with disabilities suffer a deficit in this very area in terms of comprehension, expression and cognitive skills making it difficult for them to get employed appropriately or stay employed. Vocational Rehabilitation is a continuous and coordinated process which involves the provision of vocational related services designed to enable a person with disability to obtain and maintain employment. Therefore the role of the speech language pathologist is crucial in assessing the communication deficits and needs of the individual at the various phases of employment- right from the time of seeking a job and attending interview with suitable employers and also at regular intervals of the employment. This article discusses the various communication deficits and the obstacles faced by individuals with special needs including but not limited to cognitive- linguistic deficits, execution function deficits, speech and language processing difficulties and strategies that can be introduced in the workplace to overcome these obstacles including use of visual cues, checklists, flow charts. The paper also throws light on the importance of educating colleagues and work partners about the communication difficulties faced by the individual. This would help to reduce the communication barriers in the workplace, help colleagues develop an empathetic approach and also reduce misunderstandings that can arise as a result of the communication impairment.

Keywords: vocational rehabilitation, disability, speech language pathologist, cognitive, linguistics

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Firas Alfwaress, Abdelraheem Bebers Abdelhadi Hamasha, Maha Abu Awaad

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Objectives: The aim of the present study was to investigate the effect of Palatal Lift Prosthesis (PLP) on speech clarity in patients with Flaccid Dysarthria. Five speech measures were investigated including Nasalance Scores, Diadchokinetic (DDK), Vowel Duration, airflow, and Sound Intensity. Participants: Twelve (7 Males and 5 females) native speakers of Jordanian Arabic with Flaccid Dysarthria following stroke, traumatic brain injury, and amyotrophic lateral sclerosis were included. The age of the participants ranged from 8–65 years with an average of 31.75 years. Design: Nasalance Scores, Diadchokinetic rate, Vowel Duration, and Sound Intensity were obtained using the Nasometer II, Model 6450 in three conditions. The first condition included obtaining the five measures without wearing the customized Palatal Lift Prosthesis. The second and third conditions included obtaining the five measures immediately after wearing the Palatal Lift Prosthesis and three months later. Results: Palatal lift prosthesis was found to be effective in individuals with flaccid dysarthria. Results showed decrease in the Nasalance Scores for the syllable repetition tasks and vowel prolongation tasks when comparing the means in the pre PLP with the post PLP at p≤0.001 except for the /m/ prolongation task. Results showed increased DDK repetition task, airflow amount, and sound intensity, and a decrease in vowel length at p≤0.001. Conclusions: The use of palatal lift prosthesis is effective in improving the speech of patients with flaccid dysarthria.

Keywords: palatal lift prosthesis, flaccid dysarthria, hypernasality, speech clarity, diadchokinetic rate

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Authors: Saeed Qaisrani

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This article briefly reviews the rise of Critical Discourse Analysis about the Pakistani President Mamnoon Hussain speech which delivered in the joint session of Parliament and teases out a detailed analysis of the various critiques that have been levelled at CDA and its practitioners over the last twenty years, both by scholars working within the “critical” paradigm and by other critics. A range of criticisms are discussed which target the underlying premises, the analytical methodology and the disputed areas of reader response and the integration of contextual factors. Controversial issues such as the predominantly negative focus of much CDA scholarship, and the status of CDA as an emergent “intellectual orthodoxy”, are also reviewed. The conclusions offer a summary of the principal criticisms that emerge from this overview, and suggest some ways in which these problems could be attenuated. It also focused on the different views about president speech and how it is presented in the Pakistani print and electronic media.

Keywords: Critical Discourse Analysis, Analytical methodology, Corpus linguistics, Reader response theory, Critical paradigm, Contextualization.

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Authors: Thein Thein, Kalyar Myo San

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Lip reading system is one of the different supportive technologies for hearing impaired, or elderly people or non-native speakers. For normal hearing persons in noisy environments or in conditions where the audio signal is not available, lip reading techniques can be used to increase their understanding of spoken language. Hearing impaired persons have used lip reading techniques as important tools to find out what was said by other people without hearing voice. Thus, visual speech information is important and become active research area. Using visual information from lip movements can improve the accuracy and robustness of a speech recognition system and the need for lip reading system is ever increasing for every language. However, the recognition of lip movement is a difficult task because of the region of interest (ROI) is nonlinear and noisy. Therefore, this paper proposes method to detect the accurate lips shape and to localize lip movement towards automatic lip tracking by using the combination of Otsu global thresholding technique and Moore Neighborhood Tracing Algorithm. Proposed method shows how accurate lip localization and tracking which is useful for speech recognition. In this work of study and experiments will be carried out the automatic lip localizing the lip shape for Myanmar consonants using the only visual information from lip movements which is useful for visual speech of Myanmar languages.

Keywords: lip reading, lip localization, lip tracking, Moore neighborhood tracing algorithm

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Authors: Marija Zulić, Vanda Hájková, Nina Brkić–Jovanović, Srećko Potić, Sanja Tomić

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The name cerebral palsy comes from the word cerebrum, which means the brain and the word palsy, which means seizure, and essentially refers to the movement disorder. In the clinical picture of cerebral palsy, basic neuromotor disorders are associated with other various disorders: behavioural, intellectual, speech, sensory, epileptic seizures, and bone and joint deformities. Motor speech disorders are among the most common difficulties present in people with cerebral palsy. Social participation represents an interaction between an individual and their social environment. Quality of social participation of the students with cerebral palsy at school is an important indicator of their successful participation in adulthood. One of the most important skills for the undisturbed social participation is ability of good communication. The aim of the study was to determine relation between social participation of students with cerebral palsy and presence of their speech impairment in primary schools in the Czech Republic. The study was performed in the Czech Republic in mainstream schools and schools established for the pupils with special education needs. We analysed 75 children with cerebral palsy aged between six and twelve years attending up to sixth grade by using the first and the third part of the school function assessment questionnaire as the main instrument. The other instrument we used in the research is the Gross motor function classification system–five–level classification system, which measures degree of motor functions of children and youth with cerebral palsy. Funding for this study was provided by the Grant Agency of Charles University in Prague.

Keywords: cerebral palsy, social participation, speech disorders, The Czech Republic, the school function assessment

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Alicja Zapolnik-Plachetka

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The paper examines the impact of the Members’ of the European Parliament (MEPs) language choice on the linguistic quality of their political discourse as delivered by the interpreters. The study, designed by the author, who is an EU interpreter herself, consisted of three phases. First, a number of speeches of Polish and Spanish MEPs were analyzed to determine whether the incidence of use of certain figures of speech depending on whether the speech had been delivered in English or their respective mother tongue. Then the use of figures of speech was also analyzed based on speeches by some British MEPs, in order to determine what was the incidence for the native users of English. Subsequently, the speeches were compared with their interpretations to find out whether the interpreters managed to convey accurately the means of oratory used by the MEPs. The final result shows that in case of institutional environments dependant on simultaneous interpretation the speakers’ choices can, in fact, influence the linguistic quality of the political communication.

Keywords: content accuracy, European Parliament, political discourse, simultaneous interpreting

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Authors: Nusret Mesut Sahin

Abstract:

Hrant Dink, a prominent Turkish-Armenian journalist, and editor-in-chief of the bilingual Turkish-Armenian newspaper Agos was assassinated in Istanbul on January 19th, 2007 by a nationalist extremist, Ogun Samast. Dink had been voicing the atrocities against the Armenians between 1915 and 1922 during the Ottoman rule, and his comments on the issue appeared in the Turkish media many times before his assassination. It has been argued that the suffocating atmosphere created by the Turkish news media targeting Mr. Dink made him a target of an extremist Turkish juvenile. This study analyzes the media news to understand and explain why Hrant Dink became the target of a nationalist extremist. In this research, content analysis of news articles (N= 170) is conducted to identify whether there is a link between hate speech against Hrant Dink in the Turkish media and his assassination. The content of the newspaper articles is categorized and coded according to the hate language being used. The analysis suggested that Turkish media paved the way for Dink’s assassination. Hate speech against Hrant Dink on the media had risen gradually before the assassination. The study also found that the number of news stories covering hate speech and racist discourse against non-Muslim citizens of Turkey also increased dramatically before the assassination. Therefore, hate speech against minorities in media narratives and news reports should be monitored, and political figures or leaders of social groups who are targeted by some media outlets should be protected.

Keywords: Hrant Dink, assassination, Turkish Armenian journalist, media

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Authors: Muhammad Fairul Azreen bin Mohd Zahid, Melissa Querk, Aimi Nabila bt Anizaim

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For this particular research, the focus is based on the practice as research which will produce a choreography as the outcome. The ideas organically develop as an “epiphany” from the meeting, brainstorming, or situation that revolves around surroundings. In this study, the researchers are approaching the national pillar of Malaysia known as ‘Rukun Negara’ to develop a choreographic idea. The concept theory of Speech Act by J.L Austin is used to compose the choreography alongside with national pillar ‘Rukun Negara’ as a guideline for a contemporary work titled, The Pledge 2.0, besides fostering the spirit of unity. These approaches will offer flexibility in creating a choreography piece. The pledge has crossed the boundaries by using texts and heavy issues in choreography developments. It will emphasize the concept of delivering the speech via verbal and nonverbal body language. Besides using the Theory of Speech Acts, the development process of creating this piece will lay the bare normative structure implicit in performance practice. Converging current issues into the final choreographic piece for this research is vital as this research will explore a few choreography methods from different perspectives. Hence, the audience will be able to see the world of dance that always revolves in line with the diachronic process in many ways. The method used in this research is qualitative, which will be used in finding the movement that fits the given facts.

Keywords: performing arts, speech act, performative, nationalism, choreography, politic in dance

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