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Artykuły w czasopismach na temat „American Sign Language (ASL)”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Crabtree, Margaret Ruth, and Ronnie B. Wilbur. "#ALL versus ALL in American Sign Language (ASL)." Proceedings of the Linguistic Society of America 5, no. 1 (2020): 798. http://dx.doi.org/10.3765/plsa.v5i1.4761.

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This paper extends a visible pattern (‘iconicity’) that has been observed in sign language verbs and adjectives to quantification in American Sign Language (ASL). The Event Visibility Hypothesis (EVH) states that boundedness is morphophonologically encoded in articulation of a rapid deceleration of movement at the end of a sign (aka end-marking). Here the EVH is applied to the two ASL quantifiers glossed #ALL and ALL. Doing so accounts for the semantic distinction between them: ALL is definite (bounded), whereas #ALL is underspecified for definiteness (unbounded).

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Padden, Carol A. "The ASL lexicon." Sign Language and Linguistics 1, no. 1 (1998): 39–60. http://dx.doi.org/10.1075/sll.1.1.04pad.

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This paper explores a range of Foreign vocabulary in American Sign Language and demonstrates that there are ways of accounting for them without undermining the fundamental independence of a natural sign language. Arguments are made for a unified lexicon in which Native and Foreign vocabulary are arranged schematically as extending from a core to a periphery with gradations of conformity to phonological constraints on ASL forms. At the conclusion of the paper there is a brief review of issues concerning the presence of Foreign vocabulary in natural sign languages.

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3

Pirot, Khunaw Sulaiman, and Wirya Izzaddin Ali. "The Phonological Structure of American Sign Language -ASL and zmânî âmâžaî kurdî - ZAK." Journal of University of Raparin 9, no. 4 (2022): 155–87. http://dx.doi.org/10.26750/vol(9).no(4).paper8.

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This paper deals primarily with the phonological structure of American Sign Language (ASL) and zmânî âmâžaî kurdî (ZAK) -Kurdish Sign Language. It is concerned with sign language (SL) and the types of sign language. One type is primary sign languages which are used by the Deaf people. Sign language is a visual-gestural language which relies on the use of the hands, facial expressions and body movements.Generally, there are myths about SLs. People believe that SLs are universal and have no grammatical structure. However, sign languages, as spoken languages, have lexicon, phonology, morphology a

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Stewart, Jesse. "A quantitative analysis of sign lengthening in American Sign Language." Sign Language & Linguistics 17, no. 1 (2014): 82–101. https://doi.org/10.5281/zenodo.268582.

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In spoken languages, disfluent speech, narrative effects, discourse information, and phrase position may influence the lengthening of segments beyond their typical duration. In sign languages, however, the primary use of the visual-gestural modality results in articulatory differences not expressed in spoken languages. This paper looks at sign lengthening in American Sign Language (ASL). Comparing two retellings of the Pear Story narrative from five signers, three primary lengthening mechanisms were identified: <em>elongation</em>, <em>repetition</em>, and <em>deceleration</em>. These mechanis

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5

Corina, David P., and Eva Gutierrez. "Embodiment and American Sign Language." Gesture 15, no. 3 (2016): 291–305. http://dx.doi.org/10.1075/gest.15.3.01cor.

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Little is known about how individual signs that occur in naturally produced signed languages are recognized. Here we examine whether sign understanding may be grounded in sensorimotor properties by evaluating a signer’s ability to make lexical decisions to American Sign Language (ASL) signs that are articulated either congruent with or incongruent with the observer’s own handedness. Our results show little evidence for handedness congruency effects for native signers’ perception of ASL, however handedness congruency effects were seen in non-native late learners of ASL and hearing ASL-English b

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6

Ansari, Fatima, Anwar Hussain Mistry, Yusuf Mirkar, and Alim Merchant. "Real Time ASL (American Sign Language) Recognition." International Journal of Computer Sciences and Engineering 7, no. 2 (2019): 848–51. http://dx.doi.org/10.26438/ijcse/v7i2.848851.

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Ansari, Mehtab, and Neetu Raj Bharti. "AMERICAN SIGN LANGUAGE (ASL) RECOGNITION USING OPENCV." International Journal of Engineering Applied Sciences and Technology 8, no. 2 (2023): 169–73. http://dx.doi.org/10.33564/ijeast.2023.v08i02.024.

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One of the biggest challenges for thosewho are deaf or dumb is the lack of access to communication. Here, we'll createa OpenCV based system for converting American sign language to text. Computer vision model for the dumb and deaf are a revolutionary system that has the potential to improve the quality of life for those whoare affected by hearing or speech impairments. The computer vision model will detect hand movements and translate them into text in real-time, allowing deaf and dumb individuals to communicate with others more effectively. Traditionalforms of communication such as writing ca

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8

Journal, IJSREM. "American Sign Language (ASL) Detection System using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–13. http://dx.doi.org/10.55041/ijsrem27702.

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One of the main challenges of communicating with people who have hearing disabilities is to understand their sign language. This paper presents a dedicated research project to investigate the difficulties involved in recognizing characters in American Sign Language (ASL), which is the most widely used sign language in the world. Sign language is essential for communication among people with hearing or speech impairments, but it can be hard for those who are not familiar with it, as the signs made by people with disabilities may look complicated or messy. Effective communication requires a two-

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9

Schlenker, Philippe. "Strong pronominals in ASL and LSF?" Sign Language and Linguistics 21, no. 2 (2018): 380–90. http://dx.doi.org/10.1075/sll.00025.sch.

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Abstract Theories of pronominal strength (e.g., Cardinaletti & Starke 1999) lead one to expect that sign language, just like spoken language, can have morphologically distinct strong pronominals. We suggest that American Sign Language (ASL) and French Sign Language (LSF) might have such pronominals, characterized here by the fact that they may associate with only even in the absence of prosodically marked focus.

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10

Alan, Wilson. "Sign Language to Text Conversion using CNN." Indian Journal of Data Mining (IJDM) 4, no. 1 (2024): 9–12. https://doi.org/10.54105/ijdm.A1634.04010524.

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<strong>Abstract: </strong>Sign language is a communication strategy used by those who are unable to hear. So those people who know sign language can communicate with people who are deaf. But a majority of our people don’t know sign language therefore there comes a communication gap between the ones who know sign language and others who don’t know. This project's major purpose is to bridge this gap by developing a systemthat recognizesmultiple sign languages and translates them into text in real-time. We use machine learning technologies to construct this system especially, convolu

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11

Quinto-Pozos, David. "Teaching American Sign Language to Hearing Adult Learners." Annual Review of Applied Linguistics 31 (March 2011): 137–58. http://dx.doi.org/10.1017/s0267190511000195.

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American Sign Language (ASL) has become a very popular language in high schools, colleges, and universities throughout the U.S., due, in part, to the growing number of schools that allow students to take the language in order to fulfill a foreign or general language requirement. Within the past couple decades, the number of students enrolled in ASL classes has increased dramatically, and there are likely more instructors of ASL at the present time than ever before. ASL and spoken language instruction are similar in some aspects; however, there are also differences between the two (e.g., modali

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12

Mcdermid, Campbell, and Jacob Lipps. "Conversational Regulators in American Sign Language Students." Turkish Journal of Special Education Research and Practice 6, no. 2 (2025): 1–22. https://doi.org/10.37233/trsped.2024.0149.

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Language proficiency can be framed as grammatical, sociolinguistic and strategic competency. Historically, the grammatical strategies of hearing students who study American Sign Language (ASL) have been emphasized. To address this gap, a Discourse Completion Task was designed to look at a little explored area, conversational regulators, in 14 hearing students who had taken ASL 1 (one semester) as compared to 14 hearing students who reported taking no ASL classes. Participants watched and responded to 11 videotaped contexts in ASL. The findings indicate that the ASL1 students had learned variou

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13

Stewart, Jesse. "A quantitative analysis of sign lengthening in American Sign Language." Sign Language and Linguistics 17, no. 1 (2014): 82–101. http://dx.doi.org/10.1075/sll.17.1.04ste.

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In spoken languages, disfluent speech, narrative effects, discourse information, and phrase position may influence the lengthening of segments beyond their typical duration. In sign languages, however, the primary use of the visual-gestural modality results in articulatory differences not expressed in spoken languages. This paper looks at sign lengthening in American Sign Language (ASL). Comparing two retellings of the Pear Story narrative from five signers, three primary lengthening mechanisms were identified: elongation, repetition, and deceleration. These mechanisms allow signers to incorpo

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14

G. B. Sambare. "Translating Gestures: Utilizing CNN to Enhance ASL Communication and Understanding." Journal of Electrical Systems 20, no. 6s (2024): 2724–32. http://dx.doi.org/10.52783/jes.3281.

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This research introduces a system for translating American Sign Language (ASL) utilising Convolutional Neural Networks. (CNNs). The system under consideration has the capability to identify manual gestures executed by persons communicating in American Sign Language (ASL) and subsequently convert them into written language, thereby facilitating uninterrupted communication between the deaf and hearing populations. The CNN model was validated and trained using a set of data made up of 78,300 pictures of movements in the ASL Alphabet written in American Sign Language (ASL). In order to improve the

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Chakole, Vijay V. "Educational Learning-Based Sign Language System Using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29753.

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This study proposes an innovative approach to multicultural education by integrating Indian Sign Language (ISL) and American Sign Language (ASL) through Machine Learning (ML) techniques. By collecting and preprocessing high-quality video data of ISL and ASL, we aim to develop ML models capable of recognizing and generating signs in both languages. Through bidirectional transfer learning and cross-language representation learning, we seek to enhance the learning experience and address common challenges in sign language acquisition. Additionally, personalized learning environments and culturally

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16

Mukherjee,, Prof I. T. "Transforming Expression into Language American Sign Language Recognition with Image Processing." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43306.

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The project "Transforming Expression into Language: American Sign Language Recognition using Image Processing" intends to employ image processing techniques to identify gestures in American Sign Language (ASL). The goal of this project is to develop an efficient system for translating ASL signs using visual cues generated from hand motions and gestures. The program intends to use image processing technology to bridge the communication gap between ASL users and nonusers. The use of image processing for ASL identification may improve communication in a range of situations while also increasing a

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Hardin, Belinda J., Sheresa Boone Blanchard, Megan A. Kemmery, Margo Appenzeller, and Samuel D. Parker. "Family-Centered Practices and American Sign Language (ASL)." Exceptional Children 81, no. 1 (2014): 107–23. http://dx.doi.org/10.1177/0014402914532229.

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Orfila, Lee. "A Reappraisal of the Ties Between Martha's Vineyard Sign Language and Other Sign Languages." Sign Language Studies 24, no. 4 (2024): 803–42. http://dx.doi.org/10.1353/sls.2024.a936334.

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Abstract: Martha's Vineyard Sign Language (MVSL) is an extinct village sign language hypothesized to be a sister of British Sign Language (BSL) and a significant contributor to early American Sign Language (ASL) (Groce 1985). After the last deaf MVSL signer died, signs were elicited from five hearing signers. This study analyzes that data through a series of lexicostatistical comparisons following methodology from Woodward (1978) and Guerra Currie, Meier, and Walters (2002). The results show that a sample of 711 MVSL signs is 67 percent similar to ASL, 74 percent similar to Old ASL (OASL), 56

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Pires Silva, Jorge Adriano, Carolina Carolina Morais Ribeiro da Silva, and Josiney Saraiva Pereira. "THE ASL." Periferia 16, no. 1 (2024): e86159. https://doi.org/10.12957/periferia.2024.86159.

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Teaching English to Brazilian deaf students faces specific challenges, as English is their third language, followed by Portuguese and Brazilian Sign Language (Libras) as L2/L1, respectively. Traditional English classes emphasize oral production and comprehension; thus, personalized guidance that addresses the specific linguistic needs of deaf students is lacking in national educational documents. This study highlights the importance of New Literacy Studies, advocated by Street (1984, 2000) and Barton et al. (2000), which emphasize literacy practices in diverse social and cultural contexts, cru

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20

Lucas, Ceil, and Clayton Valli. "ASL or contact signing: Issues of judgment." Language in Society 20, no. 2 (1991): 201–16. http://dx.doi.org/10.1017/s0047404500016274.

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ABSTRACTThis article reports on one aspect of an ongoing study of language contact in the American deaf community. A kind of signing that results from the contact between American Sign Language (ASL) and English exhibits features of both languages. The ultimate goal of the study is a linguistic description of contact signing and a reexamination of claims that it is a pidgin. Ten dyads and two triads of native ASL signers (6 white dyads, 4 black dyads, 2 black triads) were videotaped with a deaf interviewer, a hearing interviewer, and alone with each other. The different interview situations in

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Kentner, Ashley, and Ronnie B. Wilbur. "Wh-clefts as evidence of resultatives in ASL." Sign Language and Linguistics 21, no. 1 (2018): 77–114. http://dx.doi.org/10.1075/sll.18002.ken.

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Abstract The status of syntactic resultative constructions has been disputed in the American Sign Language (ASL) literature. These are single sentences such as “Mary hammered the metal flat,” where two predicates share the same object and an event (hammered) causes the affected object (the metal) to change state (flat) as a result. While not all languages permit such constructions, this study shows that (several) alternate multi-sentential analyses can be ruled out. WH-clefts are used to provide a test for independent clausal boundaries, providing additional support that American Sign Language

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Wattamwar, Aniket. "Sign Language Recognition using CNN." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (2021): 826–30. http://dx.doi.org/10.22214/ijraset.2021.38058.

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Abstract: This research work presents a prototype system that helps to recognize hand gesture to normal people in order to communicate more effectively with the special people. Aforesaid research work focuses on the problem of gesture recognition in real time that sign language used by the community of deaf people. The problem addressed is based on Digital Image Processing using CNN (Convolutional Neural Networks), Skin Detection and Image Segmentation techniques. This system recognizes gestures of ASL (American Sign Language) including the alphabet and a subset of its words. Keywords: gesture

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Meitantya, Mutiara Dolla, Christy Atika Sari, Eko Hari Rachmawanto, and Rabei Raad Ali. "VGG-16 ARCHITECTURE ON CNN FOR AMERICAN SIGN LANGUAGE CLASSIFICATION." Jurnal Teknik Informatika (Jutif) 5, no. 4 (2024): 1165–71. https://doi.org/10.52436/1.jutif.2024.5.4.2160.

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Every country has its sign language such as in Indonesia there are 2 types namely Indonesian Sign Language System called SIBI and BISINDO (Indonesian Sign Language). American Sign Language (ASL) is a sign language that is widely used in the world. In this research, the classification of American Sign Language (ASL) using the Convolutional Neural Network (CNN) method using VGG-16 architecture with Adam optimizer. The data used is 14000 ASL image data with 28 classes consisting of letters A to Z plus space and nothing with a division of 90% training data and 10% validation data. From this resear

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Khairnar1, Divyesh. "Real-Time Sign Language Interpretation for Inclusive Communication." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41312.

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Sign language plays a crucial role as a communication tool for both the deaf and hard-of- hearing communities, enabling them to engage and interact effectively within their own community as well as with others.However, communication barriers arise when individuals unfamiliar with sign language engage with those who rely on it, underscoring the need for inclusive solutions. Real-time sign language interpretation systems, leveraging machine learning and computer vision technologies, present a promising approach to bridging this gap. These systems convert sign language gestures into spoken or wri

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Herbert, Marjorie, and Acrisio Pires. "Bilingualism and bimodal code-blending among deaf ASL-English bilinguals." Proceedings of the Linguistic Society of America 2 (June 12, 2017): 14. http://dx.doi.org/10.3765/plsa.v2i0.4054.

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The audiologically deaf members of the American Deaf community display bilingual competence in American Sign Language (ASL) and English, although their language acquisition trajectories often involve delayed exposure to one or both languages. There is a great deal of variation in terms of production among these signers, ranging from very ASL-typical to productions that seem to display heavy English influence. The latter, mixed productions, coined “Contact Signing” by Lucas & Valli (1992), could be representative of a type of codeswitching, referred to as ‘code-blending’ in sign language-sp

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Dos Santos, Silvana Aguiar, and Hanna Beer. "Interpreting in legal contexts: Consecutive and simultaneous interpretation." Cadernos de Tradução 37, no. 2 (2017): 288. http://dx.doi.org/10.5007/2175-7968.2017v37n2p288.

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http://dx.doi.org/10.5007/2175-7968.2017v37n2p288Debra Russel, presidente da World Association of Sign Language Interpreters (WASLI) desde 2011, é uma renomada pesquisadora da área de interpretação de ASL-Inglês (American Sign Language[1][-Inglês) em contextos jurídicos. No ano de 2002, Debra publicou o livro intitulado Interpreting in legal contexts: Consecutive and simultaneous interpretation, o qual contribuiu significativamente para a formação de intérpretes de línguas de sinais que atuam no domínio jurídico. Nesse trabalho, organizado em cinco capítulos, verificam-se diversos temas pertin

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El Zaar, Abdellah, Nabil Benaya, and Abderrahim El Allati. "Sign Language Recognition: High Performance Deep Learning Approach Applyied To Multiple Sign Languages." E3S Web of Conferences 351 (2022): 01065. http://dx.doi.org/10.1051/e3sconf/202235101065.

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In this paper we present a high performance Deep Learning architecture based on Convolutional Neural Network (CNN). The proposed architecture is effective as it is capable of recognizing and analyzing with high accuracy different Sign language datasets. The sign language recognition is one of the most important tasks that will change the lives of deaf people by facilitating their daily life and their integration into society. Our approach was trained and tested on an American Sign Language (ASL) dataset, Irish Sign Alphabets (ISL) dataset and Arabic Sign Language Alphabet (ArASL) dataset and o

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Patil, Deepika, Aniket Patil, Akshay Patil, Amol More, and Suraj Shinde Patil. "Sign Language to Text Conversion." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 2613–18. http://dx.doi.org/10.22214/ijraset.2024.62147.

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Abstract: Sign language, being one of the oldest and most natural forms of communication, serves as a crucial means of expression for individuals with hearing and speech impairments. Deaf and dumb individuals heavily rely on sign language for communication, given their limitations in using spoken languages. In this context, we are introducing a real-time method utilizing neural networks for finger spelling based on American Sign Language (ASL). Automatic human gesture recognition, especially from camera images, has become an intriguing area for developing computer vision applications. Recogniz

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Fatima, Eesham, Waqasia Naeem, and Irfan Abbas. "THE INFLUENCE OF GENDER ON THE DISCOURSE MARKERS IN PAKISTANI SIGN LANGUAGE." Pakistan Journal of Social Research 04, no. 02 (2022): 1201–7. http://dx.doi.org/10.52567/pjsr.v4i2.616.

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This paper aims to shed light on the common discourse markers in Sign Language, particularly Pakistani Sign Language. Pakistani Sign Language is overlooked and emerges as a non-standardized. These gestures/ discourse markers will be studied in comparison to American Sign Language (ASL). The main features will be analysed that call for a detailed analysis based on the use, the universality and application. This research aims to study if there is any influence of gender on these discourse markers. The Pakistan Sign Language Corpus will be collected and analysed with the assistance of Sign Langua

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Bakshi, Ronit, Satwik Pandey, Tanmay Parnami, Utkarsh Jain, and Lokesh Kumar Meena. "ASL Classification using Deep learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1590–95. http://dx.doi.org/10.22214/ijraset.2023.57691.

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Abstract: In this study, the ever-evolving landscape of American Sign Language (ASL) classification is examined through the lens of cutting-edge deep learning techniques. The main objective of this research is to improve accuracy and overcome real-time constraints. For millions of individuals who are deaf or hard of hearing, sign language serves as a vital form of communication that bridges the gap between them and the rest of the world. Deep learning, specifically the use of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), has shown incredible potential in numerous c

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Sood, Dhruv. "Sign Language Recognition using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 246–49. http://dx.doi.org/10.22214/ijraset.2022.40627.

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Abstract: Millions of people with speech and hearing impairments communicate with sign languages every day. For hearingimpaired people, gesture recognition is a natural way of communicating, much like voice recognition is for most people. In this study, we look at the issue of translating/converting sign language to text and propose a better solution based on machine learning techniques. We want to establish a system that hearing-impaired people may utilise in their everyday lives to promote communication and collaboration between hearing-impaired people and people who aren't trained in Americ

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Hyun-Jong Hahm. "Agreement and Word Order in American Sign Language (ASL)." Language Facts and Perspectives 34, no. ll (2014): 57–79. http://dx.doi.org/10.20988/lfp.2014.34..57.

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Rojas-Murillo, Salvador, Alyssa B. Pancho, Michael J. Cariaso, Alexander Speicher, Alejandro Mato, and Oren Segal. "Visual learning curves for American sign language (ASL) alphabet." International Journal of Industrial Ergonomics 81 (January 2021): 103027. http://dx.doi.org/10.1016/j.ergon.2020.103027.

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Caselli, Naomi K., Zed Sevcikova Sehyr, Ariel M. Cohen-Goldberg, and Karen Emmorey. "ASL-LEX: A lexical database of American Sign Language." Behavior Research Methods 49, no. 2 (2016): 784–801. http://dx.doi.org/10.3758/s13428-016-0742-0.

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Chalcraft, Valerie J., and R. Allen Gardner. "Cross-fostered chimpanzees modulate signs of American Sign Language." Gesture 5, no. 1-2 (2005): 107–32. http://dx.doi.org/10.1075/gest.5.1-2.09cha.

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Evolutionary and developmental (Evo-Devo) biologists study the interaction between genetic endowment and developmental environment (Lewontin, 2001; Robert, 2004). Cross-fostering is a powerful tool for studying Evo-Devo. Chimpanzees lived under conditions very similar to the conditions of human children with human foster families who used American Sign Language (ASL) exclusively in their presence. In this environment, cross-fostered chimpanzees acquired and used signs as human children do. Intensive analyses of extensive video records of casual conversation show that Tatu at 46–48 months direc

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Chalcraft, Valerie J., and R. Allen Gardner. "Cross-fostered chimpanzees modulate signs of American Sign Language." Gestural Communication in Nonhuman and Human Primates 5, no. 1-2 (2005): 107–32. http://dx.doi.org/10.1075/gest.5.1.09cha.

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Evolutionary and developmental (Evo-Devo) biologists study the interaction between genetic endowment and developmental environment (Lewontin, 2001; Robert, 2004). Cross-fostering is a powerful tool for studying Evo-Devo. Chimpanzees lived under conditions very similar to the conditions of human children with human foster families who used American Sign Language (ASL) exclusively in their presence. In this environment, cross-fostered chimpanzees acquired and used signs as human children do. Intensive analyses of extensive video records of casual conversation show that Tatu at 46–48 months direc

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Drasgow, Erik. "American Sign Language as a Pathway to Linguistic Competence." Exceptional Children 64, no. 3 (1998): 329–42. http://dx.doi.org/10.1177/001440299806400303.

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Recently, it has been argued that American Sign Language (ASL) should be the first language of some deaf children and that English should be taught as a second language. This article supports that argument on both philosophical and empirical grounds. Philosophical support stems from viewing deafness as a cultural difference rather than as a medical disability. Empirical evidence demonstrates that (a) ASL is a natural language, (b) deaf children acquire ASL in a normal and predictable manner when exposure occurs at an early age, and (c) deaf children who acquire ASL at an early age may outperfo

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Holtz, Rolf. "Reading Between the Signs: Intercultural Communication for Sign Language Interpreters." Journal of International Students 4, no. 1 (2014): 106–8. http://dx.doi.org/10.32674/jis.v4i1.501.

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This book presents the subtleties of a most remarkable human attribute: The ability to understand and communicate language. The focus of the book does examine the basic elements of interpreting and translating for the deaf. However, it takes the reader far beyond the linguistic challenges of American Sign Language (ASL) into the realm of interpreting for world cultures. The book presupposes a well-developed understanding of ASL and readers are expected to already be convinced that ASL is a real language. Deaf and hearing individuals will unquestionably profit from the analyses of culture that

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Ms., H. Vaishnavi, Seetha Rama Raju SV Mr., Adaveni Nithin Mr., and Sandhya N. Dr. "Real-Time Sign Language Detection and Translation Using CNN." Journal of Scholastic Engineering Science and Management 2, no. 8 (2023): 1–11. https://doi.org/10.5281/zenodo.8170563.

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<strong>Our project focuses on the development of a computer application and the training of a model specifically  designed to interpret real-time video footage of hand gestures in American Sign Language (ASL). The primary objective  is to create a system that can accurately recognize and translate these gestures into corresponding text formats on the screen.  To achieve this, we have successfully implemented a set of 27 symbols representing the alphabet (A-Z) in ASL, along  with a symbol for blank or no gesture. Our project aims to provide a reliable and efficient tool for

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Bahan, Benjamin, Judy Kegl, Robert G. Lee, Dawn MacLaughlin, and Carol Neidle. "The Licensing of Null Arguments in American Sign Language." Linguistic Inquiry 31, no. 1 (2000): 1–27. http://dx.doi.org/10.1162/002438900554271.

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The distribution of null arguments across languages has been accounted for in terms of two distinct strategies: licensing by agreement and licensing by topic. Lillo-Martin (1986, 1991) claims that American Sign Language (ASL) exploits both strategies for licensing null arguments, depending on the morphological characteristics of the verb. Here we show that this is incorrect. Once the nonmanual correlates of agreement features (comparable to the nonmanual expressions of other syntactic features) in ASL are recognized, it becomes apparent that null arguments in this language are systematically l

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Arifullah, Mohd, Fais Khan, and Yash Handa. "REAL-TIME AMERICAN SIGN LANGUAGE RECOGNITION WITH NEURAL NETWORKS." International journal of multidisciplinary advanced scientific research and innovation 1, no. 10 (2021): 263–72. http://dx.doi.org/10.53633/ijmasri.2021.1.10.003.

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Actual-time signal language translator is a crucial milestone in facilitating communication among the deaf community and the general public. Introducing the development and use of yanked sign Language Spelling Translator (ASL) based on the convolutional neural network. We use the pre-skilled Google Net architecture educated inside the ILSVRC2012 database, in addition to the ASL database for Surrey University and Massey university ASL to apply gaining knowledge of switch in this task. We have developed a sturdy version that constantly separates the letters a-e from the original users and any ot

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Mcburney, Susan Lloyd. "William Stokoe and the discipline of sign language linguistics." Historiographia Linguistica 28, no. 1-2 (2001): 143–86. http://dx.doi.org/10.1075/hl.28.1.10mcb.

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Summary The first modern linguistic analysis of a signed language was published in 1960 – William Clarence Stokoe’s (1919–2000) Sign Language Structure. Although the initial impact of Stokoe’s monograph on linguistics and education was minimal, his work formed a solid base for what was to become a new field of research: American Sign Language (ASL) Linguistics. Together with the work of those that followed (in particular Ursula Bellugi and colleagues), Stokoe’s ground-breaking work on the structure of ASL has led to an acceptance of signed languages as autonomous linguistic systems that exhibi

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Kirthiga, Mrs N., Miriyala Vamsi Krishna, Venkata Naveen Vadlamudi, Makani Venkata Sai Kiran, and Dudekula Hussain. "Sign Language Detection Using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (2024): 1328–34. http://dx.doi.org/10.22214/ijraset.2024.58630.

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Abstract: Millions of citizens worldwide suffer from deaf and hard of hearing (DHH), a communication impairment that makes speaking difficult and necessitates the use of sign language. This communication gap frequently hampers access to education and opportunities for employment. Although AI-driven technologies have been studied to tackle this problem, no research has specifically looked into the intelligent and automatic translation of American sign gestures to text in low-resource languages (LRL), such as Nigerian languages. We suggest a unique end-to-end system for translating the American

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Janzen, Terry. "The Grammaticization of Topics in American Sign Language." Studies in Language 23, no. 2 (1999): 271–306. http://dx.doi.org/10.1075/sl.23.2.03jan.

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The topic construction of American Sign Language (ASL), within a topic-comment discourse structure framework, is explained as having emerged from gestural, communicative roots. In modern ASL, the prototypical topic construction is understood to grammatically mark pragmatic information that is accessible to both the signer and the addressee. But the construction is shown to have grammaticized further, with grammatical meaning having to do with text organization and with no reference to pragmatic, extra-linguistic information. The topic, however, is not seen as grammaticizing into a subject. Rat

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Secora, Kristen, Addison Welch, and Eva Parks. "ASL Assessment in Practice: Assessing American Sign Language Across Clinical Settings." Perspectives of the ASHA Special Interest Groups 7, no. 2 (2022): 400–417. http://dx.doi.org/10.1044/2021_persp-21-00203.

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Purpose: This exploratory research investigates the assessment tools currently used by professionals to measure receptive and expressive American Sign Language (ASL) abilities in students who are deaf/hard of hearing (DHH). Few standardized assessment tools are available for ASL and, of the limited number of tools that exist, even fewer are commercially available for professionals in the schools and clinical settings. Method: Thirty-one professionals (including speech-language pathologists, teachers of students who are DHH, ASL specialists, etc.) completed an online survey about their assessme

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Naufal, Mohammad Farid, Sesilia Shania, Jessica Millenia, et al. "Analisis Perbandingan Algoritma Klasifikasi MLP dan CNN pada Dataset American Sign Language." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (2021): 489–95. http://dx.doi.org/10.29207/resti.v5i3.3009.

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People who have hearing loss (deafness) or speech impairment (hearing impairment) usually use sign language to communicate. One of the most basic and flexible sign languages is the Alphabet Sign Language to spell out the words you want to pronounce. Sign language uses hand, finger, and face movements to speak the user's thoughts. However, for alphabetical sign language, facial expressions are not used but only gestures or symbols formed using fingers and hands. In fact, there are still many people who don't understand the meaning of sign language. The use of image classification can help peo

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Monikowski, Christine. "STORYTELLING AND CONVERSATION: DISCOURSE IN DEAF COMMUNITIES.Elizabeth Winston (Ed.). Washington, DC: Gallaudet University Press, 1999. Pp. x + 240. $55.00 cloth." Studies in Second Language Acquisition 23, no. 4 (2001): 566–67. http://dx.doi.org/10.1017/s0272263101254060.

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In this latest volume of the Sociolinguistics in Deaf Communities Series, Winston has included not only discourse analysis of American Sign Language (ASL) but also of sign languages native to Bali, Italy, and England. She offers a fascinating look at the “intricate discourse patterns that have evolved in different languages” (p. ix). Her work should be required reading for all teachers of sign language as well as teachers of interpreters. This book will also appeal to sociolinguists; language use in the community is clearly the overriding theme.

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Hilger, Allison I., Torrey MJ Loucks, David Quinto-Pozos, and Matthew WG Dye. "Second language acquisition across modalities: Production variability in adult L2 learners of American Sign Language." Second Language Research 31, no. 3 (2015): 375–88. http://dx.doi.org/10.1177/0267658315570648.

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A study was conducted to examine production variability in American Sign Language (ASL) in order to gain insight into the development of motor control in a language produced in another modality. Production variability was characterized through the spatiotemporal index (STI), which represents production stability in whole utterances and is a function of variability in effector displacement waveforms (Smith et al., 1995). Motion capture apparatus was used to acquire wrist displacement data across a set of eight target signs embedded in carrier phrases. The STI values of Deaf signers and hearing

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Perdana, I. Putu Iduar, I. Ketut Gede Darma Putra, and I. Putu Arya Dharmaadi. "Classification of Sign Language Numbers Using the CNN Method." JITTER : Jurnal Ilmiah Teknologi dan Komputer 2, no. 3 (2021): 485. http://dx.doi.org/10.24843/jtrti.2021.v02.i03.p07.

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Abstrak Berkomunikasi merupakan kebutuhan semua individu karena setiap individu harus berkomunikasi dengan lingkungan. Berkomnikasi juga membuat seseorang mendapat informasi sehingga dapat dijadikan acuan untuk beradaptasi. penggunaan bahasa verbal dengan berbicara mengeluar suara adalah cara komunikasi individu, namun hal itu tidak dapat dilakukan saat berkomunikasi dengan individu yang memilki keterbatasan dalam mendengar. Keterbatasan tersebut membuat diperlukan cara komunikasi lain yaitu melalui bahasa isyarat. Bahasa isyarat banyak jenisnya salah satunya bahasa isyarat menggunakan tangan

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Bailur, Aditi, Yesha Limbachia, Moksha Shah, Harshil Shah, and Prof Atul Kachare. "American Sign Language Recognition and its Conversion from Text to Speech." International Journal for Research in Applied Science and Engineering Technology 11, no. 9 (2023): 1533–38. http://dx.doi.org/10.22214/ijraset.2023.55871.

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Abstract: Speech impairment is a complicated condition that impairs a person's capacity for verbal and audible communication. Those who are impacted frequently use sign language and other alternate forms of communication. While sign language has gained popularity, bridging the communication gap between those who sign and those who don't remains a challenge. Our project endeavors to address this issue by developing an innovative application that offers real-time sign language-to-text translation. This technology aims to facilitate seamless communication between those who use sign language and t

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