Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective (1908.08597v1)

Abstract: Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture. Despite the need for deep interdisciplinary knowledge, existing research occurs in separate disciplinary silos, and tackles separate portions of the sign language processing pipeline. This leads to three key questions: 1) What does an interdisciplinary view of the current landscape reveal? 2) What are the biggest challenges facing the field? and 3) What are the calls to action for people working in the field? To help answer these questions, we brought together a diverse group of experts for a two-day workshop. This paper presents the results of that interdisciplinary workshop, providing key background that is often overlooked by computer scientists, a review of the state-of-the-art, a set of pressing challenges, and a call to action for the research community.

• The paper presents a comprehensive interdisciplinary analysis integrating computer vision, NLP, and HCI to address the challenges in sign language recognition, generation, and translation.
• The paper identifies key issues such as limited annotated datasets and the complexity of non-manual cues, which hinder robust and real-time processing of sign language.
• The paper calls for active collaboration with Deaf stakeholders, the creation of diverse datasets, and the development of user-friendly interface guidelines to foster practical accessibility solutions.

An Interdisciplinary Perspective on Sign Language Recognition, Generation, and Translation

The paper under review provides a comprehensive interdisciplinary analysis of sign language processing, encompassing recognition, generation, and translation. This area of research stands at the intersection of numerous fields, including computer vision, computer graphics, NLP, human-computer interaction (HCI), linguistics, and Deaf culture. The overarching aim is to bridge the technological and cultural gaps that currently restrict effective communication between Deaf and hearing populations.

Current Landscape and Challenges

The paper first outlines the current landscape of sign language processing. Critical insights reveal that despite various advancements in individual domains, integrations across disciplines remain limited. As a result, solutions are often narrow in scope and fail to address the real-world needs of Deaf communities comprehensively.

A persistent challenge in this field is the paucity of large, annotated datasets that reflect the diversity and complexity of sign languages. Existing datasets are substantially smaller than those available for speech recognition. The notable complexity of sign languages, such as their high degree of simultaneity and iconicity, exacerbates the problem of generalization across different signers and contexts. Moreover, sign languages lack a standardized written form, further complicating the process of developing robust NLP models.

Recognition systems have made strides with techniques like deep learning and convolutional neural networks (CNNs), but challenges such as depiction, generalization, and real-time processing continue to limit deployment in practical applications. Current methods struggle to capture the nuanced, non-manual elements of signing, such as facial expressions and body language, which are integral for meaning.

In translation, the lack of sufficient annotations and intermediary representations constrains the application of NLP and machine translation (MT) techniques that have transformed other language domains. Avatar generation also grapples with creating lifelike, coherent animations that respect the grammatical and semantic precision of sign languages.

Calls to Action

This paper offers several calls to action:

1. Involve Deaf Stakeholders: The authors strongly advocate for the involvement of Deaf individuals throughout the research and development process. This inclusion is crucial to ensure that solutions are culturally sensitive and address actual community needs, avoiding the pitfalls of audism.
2. Development of Real-World Applications: The research community is encouraged to concentrate efforts on applications that mirror real-world scenarios, such as enhancing accessibility in areas devoid of interpreters and developing sign language-responsive personal assistants.
3. Interface Design Guidelines: There is a call for the development of comprehensive guidelines and best practices for designing user interfaces that accommodate the needs of sign language users. This would streamline the creation of accessible technologies.
4. Creation of Large, Diverse Datasets: The generation of publicly available, extensive datasets that reflect the diversity of Deaf signers is critical. These should span different demographics and environmental conditions, to train models adept at handling real-world variability.
5. Standardized Annotation Systems: Establishing standardized annotation protocols and corresponding support tools would facilitate data sharing and improve the utility of existing corpora, while aiding in the automation of sign language corpus annotation.

Implications and Future Directions

The paper underscores the transformative potential of interdisciplinary collaboration in advancing sign language processing. The fusion of technical rigor with cultural insight is essential for developing practical, respectful, and effective technologies. As the field progresses, future research can expect to see greater strides made towards fully automated, scalable solutions that honor and encapsulate the richness of sign languages. These advancements hold the promise of significantly reducing communication barriers and fostering inclusivity.

In conclusion, while the challenges in sign language processing are substantial, the paper highlights a well-rounded, actionable path forward, thus paving the way for innovations that could profoundly impact the Deaf community globally. The calls to action resonate with both theoretical and practical considerations, providing a solid foundation for future research efforts in this vital area.