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1
Takkinen, Ritva. "Some observations on the use of HamNoSys (Hamburg Notation System for Sign Languages) in the context of the phonetic transcription of children’s signing." Language Acquisition 8, no. 1-2 (2005): 99–118. http://dx.doi.org/10.1075/sll.8.1.05tak.
Full textAbstract:
This paper discusses the use of the HamNoSys notation (Hamburg Notation System for Sign Languages) for the transcription of children’s signing. The notation system will be briefly described and some former descriptions of the acquisition of sign language phonology presented. The project in which HamNoSys was used is then described briefly followed by a description of the problems encountered while using the notation. Furthermore some proposals as to how to further develop the notation will be made. In conclusion the instrument can be said to be useful and, especially if revised, will be invaluable in further research.
2
Kaur, Khushdeep, and Parteek Kumar. "HamNoSys to SiGML Conversion System for Sign Language Automation." Procedia Computer Science 89 (2016): 794–803. http://dx.doi.org/10.1016/j.procs.2016.06.063.
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Hanke, Thomas, Reiner Konrad, and Arvid Schwarz. "GlossLexer." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 171–89. http://dx.doi.org/10.1075/sll.4.1-2.12han.
Full textAbstract:
GlossLexer is a multi-user sign language lexical database integrating digital video that has been designed to support the compilation process for specialist dictionaries from data collection to production. Sign entries are identified by HamNoSys notations as well as glosses, but the user always has immediate access to video clips showing the signs as uttered by the informants.
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Hanke, Thomas, Reiner Konrad, and Arvid Schwarz. "GlossLexer." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 171–89. http://dx.doi.org/10.1075/sll.4.12.12han.
Full textAbstract:
GlossLexer is a multi-user sign language lexical database integrating digital video that has been designed to support the compilation process for specialist dictionaries from data collection to production. Sign entries are identified by HamNoSys notations as well as glosses, but the user always has immediate access to video clips showing the signs as uttered by the informants.
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Sekarsari, Wensi, Arif Bijaksana Putra Negara, and Rudy Dwi Nyoto. "Konversi Bahasa Indonesia ke BISINDO Menggunakan JASigning dengan Metode Lookup Table." Jurnal Sistem dan Teknologi Informasi (Justin) 8, no. 3 (2020): 264. http://dx.doi.org/10.26418/justin.v8i3.38135.
Full textAbstract:
Keterbatasan jumlah juru bahasa isyarat untuk BISINDO dapat menghambat terwujudnya proses komunikasi, baik antara Teman dengar dan Teman Tuli maupun sebaliknya. Untuk mengatasi permasalahan tersebut penelitian yang dilakukan bertujuan membuat sistem yang langsung dapat mengkonversi masukan berupa teks Bahasa Indonesia (yang sebelumnya telah dibuat juga kedalam bentuk HamNoSys) menjadi gerakan isyarat BISINDO yang dapat dianimasikan dengan menggunakan JASigning. Sistem konversi yang dirancang sangat bergantung pada algoritma pencarian dan pencocokan kata dengan simbol HamNoSys pada basis data sehingga metode Lookup Table digunakan untuk menyederhanakan komputasi dan mempermudah proses konversi. Kata - kata yang digunakan untuk penelitian diambil berdasarkan frekuensi kata yang paling sering muncul dalam buku cerita “Asal Mula Kota Pontianak”. Kata – kata ini kemudian akan disusun menjadi kalimat uji yang akan digerakkan dengan menggunakan animasi 3D JASigning. Kualitas gerakan isyarat yang dihasilkan dapat diukur dengan aspek intelligibility dan acceptability dengan WER dan Skala likert sebagai instrumen penilaiannya. Hasil pengujian menunjukkan terhadap 10 Kalimat yang diujikan WER mendapatkan skor 94% dan 9 dari 10 kalimat yang diujikan mendapatkan rentang skor likert 75%-99%, ini berarti sistem konversi yang dibangun sudah memiliki intelligibility dan acceptability yang tinggi untuk gerakan isyarat BISINDO yang dihasilkan.
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Villa-Monedero, María, Manuel Gil-Martín, Daniel Sáez-Trigueros, Andrzej Pomirski, and Rubén San-Segundo. "Sign Language Dataset for Automatic Motion Generation." Journal of Imaging 9, no. 12 (2023): 262. http://dx.doi.org/10.3390/jimaging9120262.
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Several sign language datasets are available in the literature. Most of them are designed for sign language recognition and translation. This paper presents a new sign language dataset for automatic motion generation. This dataset includes phonemes for each sign (specified in HamNoSys, a transcription system developed at the University of Hamburg, Hamburg, Germany) and the corresponding motion information. The motion information includes sign videos and the sequence of extracted landmarks associated with relevant points of the skeleton (including face, arms, hands, and fingers). The dataset includes signs from three different subjects in three different positions, performing 754 signs including the entire alphabet, numbers from 0 to 100, numbers for hour specification, months, and weekdays, and the most frequent signs used in Spanish Sign Language (LSE). In total, there are 6786 videos and their corresponding phonemes (HamNoSys annotations). From each video, a sequence of landmarks was extracted using MediaPipe. The dataset allows training an automatic system for motion generation from sign language phonemes. This paper also presents preliminary results in motion generation from sign phonemes obtaining a Dynamic Time Warping distance per frame of 0.37.
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Crasborn, Onno A., Harry van der Hulst, and Els van der Kooij. "SignPhon." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 215–28. http://dx.doi.org/10.1075/sll.4.1-2.15cra.
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This paper describes the SignPhon database, a tool for phonological research. The history and goal of the project are outlined, and the database is briefly compared to other projects like HamNoSys and SignStream. We present the structure of the database and an overview of the fields that are included. We conclude with a discussion of the experiences that we have had in using the database for our research.
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Crasborn, Onno A., Harry van der Hulst, and Els van der Kooij. "SignPhon." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 215–28. http://dx.doi.org/10.1075/sll.4.12.15cra.
Full textAbstract:
This paper describes the SignPhon database, a tool for phonological research. The history and goal of the project are outlined, and the database is briefly compared to other projects like HamNoSys and SignStream. We present the structure of the database and an overview of the fields that are included. We conclude with a discussion of the experiences that we have had in using the database for our research.
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H. Aliwy, Ahmed, and Ahmed A. Alethary. "Development of arabic sign language dictionary using 3D avatar technologies." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 609. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp609-616.
Full textAbstract:
<span>The arabic sign language (ArSL) is the natural language of the deaf community in Arabic countries. ArSL suffers from a lack of resources such as unified dictionaries and corpora. In this work, a dictionary of Arabic language to ArSL has been constructed as a part of a translation system. The Arabic words are converted into hamburg notation system (HamNoSys) using eSign editor Software. HamNoSys was used to create manual parameters (handshape, hand orientation, hand location, and hand movement), while non-manual parameters (facial expressions, shoulder raising, mouthing gesture, head tilting, and body movement) added by using (mouth, face, and limbs) in the eSign editor software. The sign then converted to the sign gesture markup language (SiGML) file, and later 3D avatar interprets the SiGML file scripts to the animated sign. The constructed dictionary has three thousand signs; therefore, it can be adopted for the translation system in which written text can be transformed into sign language and can be utilized for the education of deaf people. The dictionary will be available as a free resource for researchers. It is hard and time-consuming work, but it is an essential step in machine translation of whole Arabic text to ArSL with 3D animations. </span>
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Aliwy, Ahmed H., and Ahmed A. Alethary. "Development of arabic sign language dictionary using 3D avatar technologies." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 609–16. https://doi.org/10.11591/ijeecs.v21.i1.pp609-616.
Full textAbstract:
The arabic sign language (ArSL) is the natural language of the deaf community in Arabic countries. ArSL suffers from a lack of resources such as unified dictionaries and corpora. In this work, a dictionary of Arabic language to ArSL has been constructed as a part of a translation system. The Arabic words are converted into hamburg notation system (HamNoSys) using eSign editor Software. HamNoSys was used to create manual parameters (handshape, hand orientation, hand location, and hand movement), while non-manual parameters (facial expressions, shoulder raising, mouthing gesture, head tilting, and body movement) added by using (mouth, face, and limbs) in the eSign editor software. The sign then converted to the sign gesture markup language (SiGML) file, and later 3D avatar interprets the SiGML file scripts to the animated sign. The constructed dictionary has three thousand signs; therefore, it can be adopted for the translation system in which written text can be transformed into sign language and can be utilized for the education of deaf people. The dictionary will be available as a free resource for researchers. It is hard and timeconsuming work, but it is an essential step in machine translation of whole Arabic text to ArSL with 3D animations.
11
Krammer, Klaudia, Elisabeth Bergmeister, Franz Dotter, et al. "The Klagenfurt database for sign language lexicons." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 191–201. http://dx.doi.org/10.1075/sll.4.1-2.13kra.
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The Klagenfurt database was originally developed as a base for both monolingual and bilingual dictionaries of Austrian Sign Language. The part dealing with the formational features of signs as well as the morphosyntactic and semantic information have already been finished. We decided on an approach using modified versions of Liddell & Johnson’s (1989) Movement-and-Hold model, the HamNoSys (Prillwitz, S. et al. 1989) and the SignPhon category system (Blees, M. et al. 1996).
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Krammer, Klaudia, Elisabeth Bergmeister, Franz Dotter, et al. "The Klagenfurt database for sign language lexicons." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 191–201. http://dx.doi.org/10.1075/sll.4.12.13kra.
Full textAbstract:
The Klagenfurt database was originally developed as a base for both monolingual and bilingual dictionaries of Austrian Sign Language. The part dealing with the formational features of signs as well as the morphosyntactic and semantic information have already been finished. We decided on an approach using modified versions of Liddell & Johnson’s (1989) Movement-and-Hold model, the HamNoSys (Prillwitz, S. et al. 1989) and the SignPhon category system (Blees, M. et al. 1996).
13
Joshi, Prof R. B., Shraddha Desale, Himani Gaikwad, Shamali Gunje, and Aditi Londhe. "A Survey on Sign Language Translation Systems." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 519–25. http://dx.doi.org/10.22214/ijraset.2022.41295.
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Abstract: Sign language is a way of communicating using hand gestures, movements and facial expressions, instead of spoken words. It is the medium of communication used by people who are deaf or have hearing impairments to exchange information between their own community and with normal people. In order to bridge the communication gap between people with hearing and speaking disabilities and people who do not use sign language, a lot of research work using machine learning algorithms has been done. Hence, Sign language translator came into picture. Sign Language Translators are generally used to interpret signs and gestures from deaf and hard hearing people and convert them into text. Keywords: Sign language, translator, gesture recognition, HamNoSys, Camshift, SIFT, SiGML
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Boyes-Braem, Penny. "A multimedia bilingual database for the lexicon of Swiss German Sign Language." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 133–43. http://dx.doi.org/10.1075/sll.4.1-2.10boy.
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This multimedia database project is the first large-scale collection and description of the signs of Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS). The aim of the database is to gather linguistic information on the DSGS lexicon which can serve as a basis for future dictionaries and teaching materials, as well as function as a tool for linguistic research. For each lexical entry, there is information about all of the sign’s meanings, its morphological and syntactic characteristic, several categories of usage (geographical and generation variation, style, register) as well as example links to videotaped signed sentences. The information about each lexical item is represented in the database in several different forms: Video clips of the base form of the sign and of signed sentences in which it appears, line drawings, information checkboxes, form notation (HamNoSys and SignWriting), as well as German text.
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Boyes-Braem, Penny. "A multimedia bilingual database for the lexicon of Swiss German Sign Language." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 133–43. http://dx.doi.org/10.1075/sll.4.12.10boy.
Full textAbstract:
This multimedia database project is the first large-scale collection and description of the signs of Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS). The aim of the database is to gather linguistic information on the DSGS lexicon which can serve as a basis for future dictionaries and teaching materials, as well as function as a tool for linguistic research. For each lexical entry, there is information about all of the sign’s meanings, its morphological and syntactic characteristic, several categories of usage (geographical and generation variation, style, register) as well as example links to videotaped signed sentences. The information about each lexical item is represented in the database in several different forms: Video clips of the base form of the sign and of signed sentences in which it appears, line drawings, information checkboxes, form notation (HamNoSys and SignWriting), as well as German text.
16
Miller, Christopher. "Section I." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 11–28. http://dx.doi.org/10.1075/sll.4.1-2.04mil.
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Since the original Stokoe notation, many new variants and transcription systems have been proposed: currently, HamNoSys and Stokoe derivatives are most widespread. Sign language research is in real need of a standard of its own. Exchanging data in a standard notation should save authors the time and effort needed to produce photographs, drawings or video captures illustrating data and should allow researchers to present in an explicit form the aspects of the data that are truly relevant for their purposes. Since a notation extracts from the raw data what is of interest to the researcher, it is bound to reflect certain analytical assumptions and prejudices. To maximize a notation’s usefulness, a permanent process of discussion and revision is thus necessary. Particular issues that must be dealt with in designing a sign language notation system include the distinction “internal” vs. “external” descriptions, non-manuals and simultaneous use of two hands.
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Miller, Christopher. "Section I." Sign Transcription and Database Storage of Sign Information 4, no. 1-2 (2001): 11–28. http://dx.doi.org/10.1075/sll.4.12.04mil.
Full textAbstract:
Since the original Stokoe notation, many new variants and transcription systems have been proposed: currently, HamNoSys and Stokoe derivatives are most widespread. Sign language research is in real need of a standard of its own. Exchanging data in a standard notation should save authors the time and effort needed to produce photographs, drawings or video captures illustrating data and should allow researchers to present in an explicit form the aspects of the data that are truly relevant for their purposes. Since a notation extracts from the raw data what is of interest to the researcher, it is bound to reflect certain analytical assumptions and prejudices. To maximize a notation’s usefulness, a permanent process of discussion and revision is thus necessary. Particular issues that must be dealt with in designing a sign language notation system include the distinction “internal” vs. “external” descriptions, non-manuals and simultaneous use of two hands.
18
Gil-Martín, Manuel, María Villa-Monedero, Andrzej Pomirski, Daniel Sáez-Trigueros, and Rubén San-Segundo. "Sign Language Motion Generation from Sign Characteristics." Sensors 23, no. 23 (2023): 9365. http://dx.doi.org/10.3390/s23239365.
Full textAbstract:
This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign phonemes provide information about sign characteristics like hand configuration, localization, or movements. The use of sign phonemes is crucial for generating sign motion with a high level of details (including finger extensions and flexions). The transformer-based approach also includes a stop detection module for predicting the end of the generation process. Both aspects, motion generation and stop detection, are evaluated in detail. For motion generation, the dynamic time warping distance is used to compute the similarity between two landmarks sequences (ground truth and generated). The stop detection module is evaluated considering detection accuracy and ROC (receiver operating characteristic) curves. The paper proposes and evaluates several strategies to obtain the system configuration with the best performance. These strategies include different padding strategies, interpolation approaches, and data augmentation techniques. The best configuration of a fully automatic system obtains an average DTW distance per frame of 0.1057 and an area under the ROC curve (AUC) higher than 0.94.
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Boutet, Dominique, Claudia S. Bianchini, Patrick Doan, et al. "Réflexions sur la formalisation, en tant que système, d’une transcription des formes des Langues des Signes : l’approche Typannot." SHS Web of Conferences 78 (2020): 11001. http://dx.doi.org/10.1051/shsconf/20207811001.
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Transcrire les langues des signes (LS) nécessite de prendre en considération leur nature gestuelle et de comprendre les raisons (parmi lesquelles centration sur les mains et utilisation d’un cadre de référence égocentré) pour lesquelles des systèmes typographiques (HamNoSys, SignWriting) ont échoué à s’imposer comme outil de transcription. La gestualité met en mouvement tous les segments du membre supérieur selon des degrés de liberté, en fonction d’amplitudes particulières et à travers une série de cadres de référence intrinsèque centrée sur chaque segment. Typannot, le système typographique présenté ici, repose sur ces caractéristiques et les intègre dans une hiérarchie structurelle ménageant un niveau informationnel correspondant aux traits (caractères), rassemblés dans un niveau de glyphes composés. La facilité d’utilisation de Typannot est assurée par le respect de quatre principes de conception (généricité, modularité, lisibilité et inscriptibilité) et l’utilisation d’une interface de saisie ménageant ces niveaux d’informations. Afin d’illustrer l’usage de Typannot, ont été menée des analyses portant sur les configurations et l’emplacement propre de la main, qui montrent l’influence de la gestualité praxique sur la gestualité symbolique (c.-à-d. les signes des LS). Vue la durée d’annotation encore très importante qu’un tel système de transcription impose, l’objectif est de permettre une "dictée gestuelle", une transcription directe à partir des données de capture de mouvement. Cette perspective devrait aussi faciliter la transcription de l’ensemble des gestes dits co-verbaux de n’importe quelle langue vocale.
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Begum, Ms Samreen. "Two -Way Communication Using Avatars." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50545.
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Abstract— Deaf and hard-of-hearing individuals primarily rely on sign language, which involves specific hand movements, body language, and facial expressions to communicate. However, inclusivity for this community is still lacking in various sectors, especially in educational institutions like schools and colleges. Students who are hearing-impaired often face difficulties in expressing themselves or understanding lessons in traditional classroom environments, which can lead to feels isolated. In recent years, the development of virtual avatar technology has opened new possibilities for improving communication accessibility. Sign language dictionaries today often incorporate video or animated avatar demonstrations of signs, which are more intuitive and easier to understand than static images. Some also use sign writing notations, allowing gestures to be stored in a textual format that can later be converted into visual signs using avatars. This project aims to generate sign language gestures using animated avatars. These avatars can be implemented in educational tools to help hearing individuals learn and understand sign language, making two-way communication more effective. With this technology, hearing-impaired students can participate more actively in classroom discussions, while their peers and teachers can better comprehend their input. Ultimately, this approach supports the inclusion of deaf and hard-of-hearing individuals in mainstream education and promotes equal learning opportunities. Keywords - Mediapipe hand tracking, pyttsx3 speech engine, HamNoSys notation system, SiGML (Sign Gesture Markup Language)
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Haren, Amal, Ann Reny Reema, and Rudra Prathap Boppuru. "Hand Kinesics in Indian Sign Language using NLP Techniques with SVM Based Polarity." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 4 (2020): 2044–50. https://doi.org/10.35940/ijeat.D8483.049420.
Full textAbstract:
With the advent of new technology every year, human beings continue to make clever innovations to benefit not only themselves but also those with some kind of impairment. Communication is carried out by talking to each other for regular people, but people who are deaf interact with each other through sign language. Taking this problem into account, we are proposing a methodology that allows to ease the communication with each other by translating speech into sign language. This paper explains a methodology that translates speech into the corresponding Indian Sign Language (ISL). In India, it is spoken in almost 28 different languages. So, language has always been a problem. Thus, we have come with a project just for India in which the person can communicate with the app in any Indian language they know, and it will convert it into Indian Sign Language. This is applicable to not just literate but also illiterate people across India. The idea is to take the speech input and translate to text, which will then undergo text-pre-processing using NLP for better analysis and will be connected to the HamNoSys data for the generation of sign languages. The polarity detection will also be included. It is implemented using the SVM algorithm for Sentimental Analysis. Thus, the main objective of this project is to develop a useful project which can be used to capture the whole vocabulary of Indian Sign Language (ISL) and provide access to information and services to mute people in ISL.
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Sugandhi, Kumar Parteek, and Kaur Sanmeet. "Online Multilingual Dictionary Using Hamburg Notation for Avatar-Based Indian Sign Language Generation System." International Journal of Business, Human and Social Sciences 11.0, no. 8 (2018). https://doi.org/10.5281/zenodo.1474397.
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Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.
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Marshall, Ian, and Eva Safar. "Sign language generation in an ALE HPSG." Proceedings of the International Conference on Head-Driven Phrase Structure Grammar, October 18, 2004. http://dx.doi.org/10.21248/hpsg.2004.11.
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During the past fifty years sign languages have been recognised as genuine languages with their own syntax and distinctive phonology. In the case of sign languages, phonetic description characterises the manual and non-manual aspects of signing. The latter relate to facial expression and upper torso position. In the case of manual components these characterise hand shape, orientation and position, and hand/arm movement in three dimensional space around the signer's body. These phonetic charcaterisations can be notated as HamNoSys descriptions of signs which has an executable interpretation to drive an avatar. The HPSG sign language generation component of a text to sign language system prototype is described. The assimilation of SL morphological features to generate signs which respect positional agreement in signing space are emphasised.
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Mami, Amine, Mohamed Elfares Slimani, Taha Zerrouki, and Redha Mazari. "Arabic Algerian Sign Language Translation System Based on 3D Avatar Technology." Nafath 9, no. 28 (2024). https://doi.org/10.54455/mcn2804.
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This work focuses on the creation of tools to help deaf people learn Arabic Algerian Sign Language (ALSL), specifically an automatic translation system with a 3D avatar for accurate and dynamic sign representation. The system encodes ALSL signs using the Notation System Method (NSM), which is principally based on the Hamburg Notation System (HamNoSys). A shallow analysis of the linguistic complexity of ALSL is offered, as well as the obstacles inherent in developing technological solutions to facilitate proper translation. To ensure correctness, the development approach involved working with ALSL translation experts at each level. The system's lexicon, consisting of 417 words, achieved a certified accuracy rate of 75.53%. These results represent a substantial step forward in 3D avatar-based sign language simulation, with opportunities for further refinement and development.
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"Sign Language Generation - A survey of techniques." Regular 9, no. 9 (2020): 473–76. http://dx.doi.org/10.35940/ijitee.i7244.079920.
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Sign language is a visual language that uses body postures and facial expressions. It is generally used by hearing-impaired people as a source of communication. According to the World Health Organization (WHO), around 466 million people (5% of the world population) are with hearing and speech impairment. Normal people generally do not understand this sign language and hence there is a communication gap between hearing-impaired and other people. Different phonemic scripts were developed such as HamNoSys notation that describes sign language using symbols. With the development in the field of artificial intelligence, we are now able to overcome the limitations of communication with people using different languages. Sign language translating system is the one that converts sign to text or speech whereas sign language generating system is the one that converts speech or text to sign language. Sign language generating systems were developed so that normal people can use this system to display signs to hearing-impaired people. This survey consists of a comparative study of approaches and techniques that are used to generate sign language. We have discussed general architecture and applications of the sign language generating system.
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"Hand Kinesics in Indian Sign Language using NLP Techniques with SVM Based Polarity." International Journal of Engineering and Advanced Technology 9, no. 4 (2020): 2044–51. http://dx.doi.org/10.35940/ijeat.d8483.049420.
Full textAbstract:
With the advent of new technology every year, human beings continue to make clever innovations to benefit not only themselves but also those with some kind of impairment. Communication is carried out by talking to each other for regular people, but people who are deaf interact with each other through sign language. Taking this problem into account, we are proposing a methodology that allows to ease the communication with each other by translating speech into sign language. This paper explains a methodology that translates speech into the corresponding Indian Sign Language (ISL). In India, it is spoken in almost 28 different languages. So, language has always been a problem. Thus, we have come with a project just for India in which the person can communicate with the app in any Indian language they know, and it will convert it into Indian Sign Language. This is applicable to not just literate but also illiterate people across India. The idea is to take the speech input and translate to text, which will then undergo text-pre-processing using NLP for better analysis and will be connected to the HamNoSys data for the generation of sign languages. The polarity detection will also be included. It is implemented using the SVM algorithm for Sentimental Analysis. Thus, the main objective of this project is to develop a useful project which can be used to capture the whole vocabulary of Indian Sign Language (ISL) and provide access to information and services to mute people in ISL.
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González Hernández, Norma, Susan Rodríguez González, Lidia Maria Prado Lopez, and Gabriela Alejandra Lopez Robles. "Parte 2: Manejo de la Alergia a la Proteína de Leche de Vaca." Acta Pediátrica Hondureña, March 31, 2017, 670–80. http://dx.doi.org/10.5377/pediatrica.v7i2.6964.
Full textAbstract:
La lactancia materna es un excelente factor protector y una forma inigualable de facilitar el alimento ideal para el crecimiento y desarrollo saludable. Es imprescindible su recomendación exclusiva durante los primeros 6 meses de vida y de ser posible continuar con la lactancia materna durante la alimentación complementaria hasta los 2 años de edad; solo se debe recurrir a fórmulas especiales cuando la madre no pueda amamantar. Para estos casos se dispone de varias fórmulas hidrolizadas, soja y elementales. Las fórmulas hidrolizadas pueden ser extensa o parcialmente hidrolizadas, y ser séricas o de caseína. Las fórmulas extensamente hidrolizadas, han sido sometidas a ensayos clínicos donde se comprueba su hipoalergenicidad al eliminar los síntomas de la Alergia a la Proteína de la Leche de Vaca (APLV) luego de su inicio. Estudios recientes demuestran que la adición de Lactobacillusr hamnosus (LGG) a una fórmula de caseína extensamente hidrolizada acelera la adquisición de tolerancia en estos niños en comparación con los pacientes que recibieron fórmula sin adición. La fórmula de soja, aunque no es hipoalergénica, se puede emplear para tratar la APLV, pero no antes de los 6 meses. No se pueden emplear como tratamiento de APLV fórmulas parcialmente hidrolizadas, ni leche de otros rumiantes, como oveja o cabra. En pacientes con altos niveles de sensibilización o con antecedente de reacción anafiláctica, se recomienda la administración de fórmula elemental. El objetivo de la presente revisión es dar a conocer el manejo y uso racional de las fórmulas hidrolizadas y elementales en niños con APLV y así evitar el uso indiscriminado de estas en niños con trastornos funcionales.Palabras clave Fórmulas infantiles, hidrolizados de proteína, Lactobacillus rhamnosus, leche de soja, aminoácidos