Integration of a Spanish-to-LSE machine translation system into an e-learning platform

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-21657-2_61This paper presents the first results of the integration of a Spanish-to-LSE Machine Translation (MT) system into an e-learning platform. Most e-learning platforms provide speech-based contents, which makes them inaccessible to the Deaf. To solve this issue, we have developed a MT system that translates Spanish speech-based contents into LSE. To test our MT system, we have integrated it into an e-learning tool. The e-learning tool sends the audio to our platform. The platform sends back the subtitles and a video stream with the signed translation to the e-learning tool. Preliminary results, evaluating the sign language synthesis module, show an isolated sign recognition accuracy of 97%. The sentence recognition accuracy was of 93%.Authors would like to acknowledge the FPU-UAM grant program for its financial support. Authors are grateful to the FCNSE linguistic department for sharing their knowledge in LSE and performing the evaluations. Many thanks go to María Chulvi and Benjamín Nogal for providing help during the imple-mentation of this system. This work was partially supported by the Telefónica Móviles España S.A. project number 10-047158-TE-Ed-01-1

Konversi Bahasa Indonesia ke BISINDO Menggunakan JASigning dengan Metode Lookup Table

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

A Study on Techniques and Challenges in Sign Language Translation

Sign Language Translation (SLT) plays a pivotal role in enabling effective communication for the Deaf and Hard of Hearing (DHH) community. This review delves into the state-of-the-art techniques and methodologies in SLT, focusing on its significance, challenges, and recent advancements. The review provides a comprehensive analysis of various SLT approaches, ranging from rule-based systems to deep learning models, highlighting their strengths and limitations. Datasets specifically tailored for SLT research are explored, shedding light on the diversity and complexity of Sign Languages across the globe. The review also addresses critical issues in SLT, such as the expressiveness of generated signs, facial expressions, and non-manual signals. Furthermore, it discusses the integration of SLT into assistive technologies and educational tools, emphasizing the transformative potential in enhancing accessibility and inclusivity. Finally, the review outlines future directions, including the incorporation of multimodal inputs and the imperative need for co-creation with the Deaf community, paving the way for more accurate, expressive, and culturally sensitive Sign Language Generation systems

Artificial Intelligence for Multimedia Signal Processing

Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining