Search results for: speech language therapy

Authors: Mile Vuković, Lana Jerkić Rajić

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Introduction: Broca's aphasia is a non-fluent type of aphasic syndrome, which is primarily manifested by impairment of language production. In connected speech, patients with this type of aphasia produce short sentences in which they often omit function words and morphemes or choose inadequate forms. Aim: This research was conducted to examine the morphosyntactic abilities of people with Broca's aphasia, comparing them with neurologically healthy subjects without a language disorder. Method: The sample included 15 patients with Broca's post-stroke aphasia, who had the relatively intact ability of auditory comprehension. The diagnosis of aphasia was based on the Boston Diagnostic Aphasia Examination. The control group comprised 16 neurologically healthy subjects without data on the presence of disorders in speech and language development. The patients' mother tongue was Serbian. The new Serbian Morphosyntactic Abilities Test (SMAT) was used. Descriptive (frequency, percentage, mean, SD, min, max) and inferential (Mann-Whitney U-test) statistics were used in data processing. Results: We noticed statistically significant differences between people with Broca's aphasia and neurotypical subjects on the SMAT (U = 1.500, z = -4.982, p = 0.000). The results showed that people with Broca's aphasia had achieved low scores on the SMAT, regardless of age (ρ = -0.045, p = 0.873) and time post onset (ρ = 0.330, p = 0.229). Conclusion: Preliminary results show that the SMAT has the potential to detect morphosyntactic deficits in Serbian speakers with Broca's aphasia.

Keywords: Broca’s aphasia, morphosyntactic abilities, agrammatism, Serbian language

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Authors: Thapasya J., Rajesh Kumar

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

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

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Authors: Tamara Matevosyan

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The present paper discusses the main problems that students face while developing oral skills through authentic films. It states that special attention should be paid not only to the study of verbal speech but also to non-verbal communication. Authentic films serve as an important tool to understand both native speaker’s gestures and their culture of pausing while speaking. Various phonetic difficulties causing phonetic interference in actual speech are covered in the paper emphasizing the role of authentic films in overcoming them.

Keywords: compressive speech, filled pauses, unfilled pauses, pausing culture

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Authors: Shamm Kidane, Ibrahim Abdella, Fitsum Gaim, Simon Mulugeta, Sirak Asmerom, Natnael Ambasager, Yoel Ghebrihiwot

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The call for natural language processing (NLP) systems for low-resource languages has become more apparent than ever in the past few years, with the arduous challenges still present in preparing such systems. This paper presents an improved dataset version of the Nagaoka Tigrinya Corpus for Parts-of-Speech (POS) classification system in the Tigrinya language. The size of the initial Nagaoka dataset was incremented, totaling the new tagged corpus to 118K tokens, which comprised the 12 basic POS annotations used previously. The additional content was also annotated manually in a stringent manner, followed similar rules to the former dataset and was formatted in CONLL format. The system made use of the novel approach in NLP tasks and use of the monolingually pre-trained TiELECTRA, TiBERT and TiRoBERTa transformer models. The highest achieved score is an impressive weighted F1-score of 94.2%, which surpassed the previous systems by a significant measure. The system will prove useful in the progress of NLP-related tasks for Tigrinya and similarly related low-resource languages with room for cross-referencing higher-resource languages.

Keywords: Tigrinya POS corpus, TiBERT, TiRoBERTa, conditional random fields

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Authors: Xharavina V., Gallopeni F., Ahmeti K.

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Stuttered speech is filled with intermittent sound prolongations and/or rapid part word repetitions. Oftentimes, these aberrant acoustic behaviors are associated with intermittent physical tension and struggle behaviors such as head jerks, arm jerks, finger tapping, excessive eye-blinks, etc. Additionally, the jarring nature of acoustic and physical manifestations that often accompanies moderate-severe stuttering may induce negative emotional responses in listeners, which alters communication between the person who stutters and their listeners. However, researches for the influence of negative emotions in the communication and for physical reaction are limited. Therefore, to compare psycho-physiological responses of fluent adults, while listening the speech of adults who speak fluency and adults who stutter, are necessary. This study comprises the experimental method, with total of 104 participants (average age-20 years old, SD=2.1), divided into 3 groups. All participants self-reported no impairments in speech, language, or hearing. Exploring the responses of the participants, there were used two records speeches; a voice who speaks fluently and the voice who stutters. Heartbeats and the pulse were measured by the digital blood pressure monitor called 'Tensoval', as a physiological response to the fluent and stuttering sample. Meanwhile, the emotional responses of participants were measured by the self-reporting questionnaire (Steenbarger, 2001). Results showed an increase in heartbeats during the stuttering speech compared with the fluent sample (p < 0.5). The listeners also self-reported themselves as more alive, unhappy, nervous, repulsive, sad, tense, distracted and upset when listening the stuttering words versus the words of the fluent adult (where it was reported to experience positive emotions). These data support the notions that speech with stuttering can bring a psycho-physical reaction to the listeners. Speech pathologists should be aware that listeners show intolerable physiological reactions to stuttering that remain visible over time.

Keywords: emotional, physiological, stuttering, fluent speech

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Authors: Ahmed Elgadri

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

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

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Authors: Gobinathan Devathasan, Kezia Devathasan

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Objective: To improve the current modified Broca-Wernicke-Lichtheim-Kussmaul speech schema and provide insight into autism. Methods: We reviewed the pertinent literature. Current findings, involving Brodmann areas 22, 46, 9,44,45,6,4 are based on neuropathology and functional MRI studies. However, in primary autism, there is no lucid explanation and changes described, whether neuropathology or functional MRI, appear consequential. Findings: We forward an enhanced model which may explain the enigma related to autism. Vowel output is subcortical and does need cortical representation whereas consonant speech is cortical in origin. Left lateralization is needed to commence the circuitry spin as our life have evolved with L-amino acids and left spin of electrons. A fundamental species difference is we are capable of three syllable-consonants and bi-syllable expression whereas cetaceans and songbirds are confined to single or dual consonants. The 4 key sites for speech are superior auditory cortex, Broca’s two areas, and the supplementary motor cortex. Using the Argand’s diagram and Reimann’s projection, we theorize that the Euclidean three dimensional synaptic neuronal circuits of speech are quantized to coherent waves, and then decoherence takes place at area 6 (spherical representation). In this quantum state complex, 3-consonant languages are instantaneously integrated and multiple languages can be learned, verbalized and differentiated. Conclusion: We postulate that evolutionary human speech is elevated to quantum interaction unlike cetaceans and birds to achieve the three consonants/bi-syllable speech. In classical primary autism, the sudden speech switches off and on noted in several cases could now be explained not by any anatomical lesion but failure of coherence. Area 6 projects directly into prefrontal saccadic area (8); and this further explains the second primary feature in autism: lack of eye contact. The third feature which is repetitive finger gestures, located adjacent to the speech/motor areas, are actual attempts to communicate with the autistic child akin to sign language for the deaf.

Keywords: quantum neuronal paradigm, cetaceans and human speech, autism and rapid magnetic stimulation, coherence and decoherence of speech

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Authors: Shibo Wei, Ting Jiang

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Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

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Authors: Jummai Aliyu Mohammed

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The Sapir-Whorfian hypothesis postulates that the structure of a language determines the way in which species of that language view the world. It also states that the culture of a people finds reflection in their language. Consequently language becomes a vehicle of thought; a channel through which negative stereotypes of women is created and also one through which such images are dispelled. Women are generally portrayed as weaker vessels and inferior to men; a position which draws a counter reaction from women through their writings. In their writings, they attempt to reinvent womanhood and liberate the woman from the hitherto negative light they were portrayed. This position best describes the term feminism which argues that women be given equal rights in all spheres of life as men. This paper attempts to evaluate Ba’s ‘So Long a Letter’ and Alkali’s ‘The Stillborn’ with the view to identify the relationship between language and feminism. In evaluating this relationship, the paper concludes that there are several factors responsible for the variation in the speech pattern of male and female. All of these factors favour the male gender and further condemns the woman to oppression. Although the writers come from two different cultural backgrounds, the works amplify feminism and captured them as apostles of feminism.

Keywords: feminism, language, politics, Sapir-Whorfian hypothesis

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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: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Ana Londral, Burcu Demiray, Marcus Cheetham

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Speech recording is a methodology used in many different studies related to cognitive and behaviour research. Modern advances in digital equipment brought the possibility of continuously recording hours of speech in naturalistic environments and building rich sets of sound files. Speech analysis can then extract from these files multiple features for different scopes of research in Language and Communication. However, tools for analysing a large set of sound files and automatically extract relevant features from these files are often inaccessible to researchers that are not familiar with programming languages. Manual analysis is a common alternative, with a high time and efficiency cost. In the analysis of long sound files, the first step is the voice segmentation, i.e. to detect and label segments containing speech. We present a comprehensive methodology aiming to support researchers on voice segmentation, as the first step for data analysis of a big set of sound files. Praat, an open source software, is suggested as a tool to run a voice detection algorithm, label segments and files and extract other quantitative features on a structure of folders containing a large number of sound files. We present the validation of our methodology with a set of 5000 sound files that were collected in the daily life of a group of voluntary participants with age over 65. A smartphone device was used to collect sound using the Electronically Activated Recorder (EAR): an app programmed to record 30-second sound samples that were randomly distributed throughout the day. Results demonstrated that automatic segmentation and labelling of files containing speech segments was 74% faster when compared to a manual analysis performed with two independent coders. Furthermore, the methodology presented allows manual adjustments of voiced segments with visualisation of the sound signal and the automatic extraction of quantitative information on speech. In conclusion, we propose a comprehensive methodology for voice segmentation, to be used by researchers that have to work with large sets of sound files and are not familiar with programming tools.

Keywords: automatic speech analysis, behavior analysis, naturalistic environments, voice segmentation

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Authors: Esha Banerjee, Atul Kumar Ojha, Girish Nath Jha

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This study aims to develop an intonation labeled database for Hindi. Although no single standard for prosody labeling exists in Hindi, researchers in the past have employed perceptual and statistical methods in literature to draw inferences about the behavior of prosody patterns in Hindi. Based on such existing research and largely agreed upon intonational theories in Hindi, this study attempts to develop a manually annotated prosodic corpus of Hindi speech data, which can be used for training speech models for natural-sounding speech in the future. 100 sentences ( 500 words) each for declarative and interrogative types have been labeled using Praat.

Keywords: speech dataset, Hindi, intonation, labeled corpus

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Authors: Carmela Perta

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In Italy the coexistence of standard language, its varieties and different minority languages - historical and migration languages - has been a way to study language contact in different directions; the focus of most of the studies is either the relations among the languages of the social repertoire, or the study of contact phenomena occurring in a particular structural level. However, studies on contact facts in relation to a given sociolinguistic situation of the speech community are still not present in literature. As regard the language level to investigate from the perspective of contact, it is commonly claimed that the lexicon is the most volatile part of language and most likely to undergo change due to superstrate influence, indeed first lexical features are borrowed, then, under long term cultural pressure, structural features may also be borrowed. The aim of this paper is to analyse language contact in two historical minority communities where Francoprovençal is spoken, in relation to their sociolinguistic situation. In this perspective, firstly lexical borrowings present in speakers’ speech production will be examined, trying to find a possible correlation between this part of the lexicon and informants’ sociolinguistic variables; secondly a possible correlation between a particular community sociolinguistic situation and lexical borrowing will be found. Methods used to collect data are based on the results obtained from 24 speakers in both the villages; the speaker group in the two communities consisted of 3 males and 3 females in each of four age groups, ranging in age from 9 to 85, and then divided into five groups according to their occupations. Speakers were asked to describe a sequence of pictures naming common objects and then describing scenes when they used these objects: they are common objects, frequently pronounced and belonging to semantic areas which are usually resistant and which are thought to survive. A subset of this task, involving 19 items with Italian source is examined here: in order to determine the significance of the independent variables (social factors) on the dependent variable (lexical variation) the statistical package SPSS, particularly the linear regression, was used.

Keywords: borrowing, Francoprovençal, language change, lexicon

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Authors: Festa Shabani

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This paper aims at investigating bilingual speech in the International Schools of Prishtina. More particularly, it seeks to analyze bilingual phenomena among adolescent students highly exposed to English with the latter as the language of instruction at school in naturally-occurring conversations within school environment. Adolescence was deliberately chosen since it is regarded as an age when peer influence on language choice is the greatest. Driven by daily unsystematic observation and prior research already undertaken, the hypothesis stated is that Albanian continues to be the dominant language among Prishtina international schools’ students with a lot of code-switched items from the English. Furthermore, they will also use lexical borrowings - words already adapted in the receiving language, from the language they have been in contact with, in their speech often in the lack of existing equivalents in Albanian or for other reasons. This is done owing to the fact that the language of instruction at school is English, and any topic related to the language they have been exposed to will trigger them to use English. Therefore, this needs special attention in an attempt to identify patterns of their speech; in this way, linguistic and socio-pragmatic factors will be considered when analyzing the motivations behind their language choice. Methodology for collecting data include participant systematic observation and tape-recording. While observing them in their natural conversations, the fieldworker also took notes, which helped transcribe details better. The paper starts by raising the question of whether code-switching is occurring among Prishtina International Schools’ students highly exposed to English. The data gathered from students in informal settings suggests that there are well-founded grounds for an affirmative answer. The participants in this study are observed to be code-switching, although showing differences in degree. However, a generalization cannot be made on the basis of the findings except in so far it appears that English has, in turn, became a language to which they turn when identifying with the group when discussing about particular school topics. Particularly, participants seemed to use intra-sentential CS in cases when they seem to find an English expression rather easier than an Albanian one when repeating or emphasizing a point when urged to talk about educational issues with English being their language of instruction, and inter-sentential code-switching, particularly when quoting others. Concerning the grammatical aspect of code-switching, the intrasentential CS is used more than the intersentetial one. Speaking of gender, the results show that there were really no significant differences in regards quantity between male and female participants. However, the slight tendency for men to code switch intrasententially more than women was manifested. Similarly, a slight tendency again for a difference to emerge is on intersentential switching, which contributes 21% to the total number of switches for women, but 11% to the total number of switches for men.

Keywords: Albanian, code-switching contact linguistics, bilingual phenomena, lexical borrowing, English

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

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Authors: M. Kiran Reddy, K. Sreenivasa Rao

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The conventional Hidden Markov Model (HMM)-based speech synthesis system (HTS) uses only a pulse excitation model, which significantly differs from natural excitation signal. Hence, buzziness can be perceived in the speech generated using HTS. This paper proposes an efficient excitation modeling method that can significantly reduce the buzziness, and improve the quality of HMM-based speech synthesis. The proposed approach models the pitch-synchronous residual frames extracted from the residual excitation signal. Each pitch synchronous residual frame is parameterized using 30 wavelet coefficients. These 30 wavelet coefficients are found to accurately capture the perceptually important information present in the residual waveform. In synthesis phase, the residual frames are reconstructed from the generated wavelet coefficients and are pitch-synchronously overlap-added to generate the excitation signal. The proposed excitation modeling method is integrated into HMM-based speech synthesis system. Evaluation results indicate that the speech synthesized by the proposed excitation model is significantly better than the speech generated using state-of-the-art excitation modeling methods.

Keywords: excitation modeling, hidden Markov models, pitch-synchronous frames, speech synthesis, wavelet coefficients

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Authors: Jalal Karam

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The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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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: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

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Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

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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: Samaneh serraj

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Listening anxiety has a detrimental effect on language learners. Through a qualitative study on Iranian EFL learners several factors were identified as having influence on their listening anxiety. These factors were divided into three categories, i.e. individual factors (nerves and emotionality, using inappropriate strategies and lack of practice), input factors (lack of time to process, lack of visual support, nature of speech and level of difficulty) and environmental factors (instructors, peers and class environment).

Keywords: listening Comprehension, Listening Anxiety, Foreign language learners

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Authors: Mercy Itohan Aruya

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This paper focuses on Usen, a speech form enclaved by the Edo communities in Ovia South West Local Government Area of Edo State, Nigeria. Usen lies at the border between Edo and the Osun state in Nigeria and has a population size of about a hundred and eighty thousand native speakers (2006 population census of Nigeria). Usen, as it is spoken today is highly endangered and it is serious struggling for survival. The aim, therefore, is to ascertain the linguistics status of Usen using a lexicostatical approach. Lexicostatics is a linguistic technique employed in accessing the degree of linguistic divergence or relatedness between two or more languages based on the proportion of cognates. Data for this study were collected from competent native speakers whose ages fall within the range of 40-65. The instrument for this study is the Ibadan 400 word-list of basic items which are collected with of a digital voice recorder. Our major finding in this paper reveals and establishes the facts that Usen speech form is not a dialect but a language of its own. However, Usen is more related to Yoruba than Edo as the degree of relatedness between Usen and Yoruba is 56.14% while that between Usen and Edo is about 21.4% as shown in this research effort.

Keywords: Usen, lexicostatistics, cognate words, language status

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Sukhvinder Singh

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Punjabi language is related to the languages of New Indo-Aryan group that, in turn, is related to the branch of Indo-European language family. Punjabi language covers the areas of Western part (that is in Pakistan) and Eastern part (the Punjab state, Haryana, Delhi Himachal and J&K) and abroad (particularly Canada, USA, U.K. and Arab Emirates), where it is spoken widely. Besides India and Pakistan, Punjabi is the third language spoken in Canada after English, French having more than one hundred millions speakers worldwide. It is the fourth language spoken in Canada after English, French, and Chinese. It is also being taught as second language in most of the community school of British Columbia. The total number of Punjabi speakers is more than one hundred millions including India, Pakistan and abroad. Punjabi has a long tradition of linguistic tradition. A large number of scholars have studied Punjabi at different linguistic levels. Various studies are devoted to its special phonological characteristics, especially the tone, which has now started disappearing in favour of aspiration, a rare example of a language change in progress in its reversal direction. This process of language change in progress in reversal is dealt with in this paper a change towards a loss of linguistic indigeneity. The tone being a distinctive linguistic feature of Punjabi language is getting lost due to the increasing influence of Hindi and English particularly in the speech Urban Punjabi and Punjabi settled abroad. In this paper, an attempt has been made to discuss the sociolinguistics and sociology of Punjabi language and Punjab to trace the initiation and progression of this change towards a loss of Linguistic Indigeneity.

Keywords: language change in reversal, reaspiration, detonalization, new Indo-Aryan group

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Authors: Rasha Alsabbah

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This study explores the relationship between polite language use and religion in the Iraqi culture in computer mediated communication. It tackles the speech acts where these expressions are employed, the frequency of their occurrence and the aims behind them. It also investigates if they have equivalent expressions in English and the possibility of translating them in intercultural communication. Despite the wide assumption that language is a reflection of culture and religion, it started to grant the attention sociologists during the recent 40 years when scholars have questioned the possible interconnection between religion and language in which religion is used as a mean of producing language and performing pragmatic functions. It is presumed that Arabs in general, and Iraqis in particular, have an inclination to use religious vocabulary in showing politeness in their greeting and other speech acts. Due to Islamic religion and culture’s influences, it is observed that Iraqis are very much concerned of maintaining social solidarity and harmonious relationships which make religion a politeness strategy that operates as the key point of their social behaviours. In addition, religion has found to influence almost all their interactions in which they have a tendency of invoking religious expressions, the lexicon of Allah (God), and Qur’anic verses in their daily politeness discourse. This aspect of Islamic culture may look strange, especially to people who come from individualist societies, such as England. Data collection in this study is based on messaging applications like Viber, WhatsApp, and Facebook. After gaining the approval of the participants, there was an investigation for the different aims behind these expressions and the pragmatic function that they perform. It is found that Iraqis tend to incorporate the lexicon of Allah in most of their communication. Such employment is not only by religious people but also by individuals who do not show strong commitment to religion. Furthermore, the social distance and social power between people do not play a significant role in increasing or reducing the rate of using these expressions. A number of these expressions, though can be translated into English, do not have one to one counterpart or reflect religious feeling. In addition, they might sound odd upon being translated or transliterated in oral and written communication in intercultural communication.

Keywords: computer mediated communication (CMC), intercultural communication, politeness, religion, situation bound utterances rituals, speech acts

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Authors: Mohamed Sharof Mostafa, Atefeh Ahmadi

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Most of traditional single modality psychotherapy and counselling approaches to clients’ problems are based on the application of one therapy in all sessions. Modern developments in these sciences focus on eclectic and integrative interventions to consider all dimensions of an issue and all characteristics of the clients. This paper presents and overview eclectic therapy and its pros and cons. In addition, multiple intelligence theory and its application in eclectic therapy approaches are mentioned.

Keywords: eclectic therapy, client, multiple intelligence theory, dimensions

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

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