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What are the biggest challenges in creating computational linguistics applications for sign languages?

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Computational linguistics is the field of study that explores the interaction between natural languages and computers. It involves developing applications that can process, analyze, and generate language data, such as speech recognition, machine translation, natural language understanding, and text summarization. However, most of these applications are designed for spoken and written languages, and not for sign languages, which are visual-spatial languages that use gestures, facial expressions, and body movements to communicate. Sign languages are used by millions of deaf and hard-of-hearing people around the world, and they have their own grammatical structures, lexical items, and cultural norms. In this article, you will learn about some of the biggest challenges in creating computational linguistics applications for sign languages, and how researchers and developers are trying to overcome them.

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Ivan Crespo

ESL teacher & Teacher Educator at the University of Illinois, Intensive English Institute | Specialist in Educational…

1 Data scarcity

One of the main challenges in creating computational linguistics applications for sign languages is the lack of data. Unlike spoken and written languages, which have large corpora of texts and audio recordings, sign languages have relatively few digital resources that can be used for training and testing algorithms. This is because sign languages are not standardized, and they vary across regions, communities, and individuals. Moreover, sign languages are difficult to capture and annotate, as they require specialized equipment, such as cameras, sensors, and gloves, and human experts, who can transcribe and label the signs, facial expressions, and body movements. Therefore, there is a need for more data collection and annotation efforts, as well as methods for data augmentation and sharing, to enable the development of robust and accurate computational linguistics applications for sign languages.

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Ivan Crespo

ESL teacher & Teacher Educator at the University of Illinois, Intensive English Institute | Specialist in Educational Technology & ESL Pronunciation
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Creating computer programs for sign languages faces a big problem – there's not enough information. Unlike spoken and written languages, which have lots of words and recordings, sign languages don't have much digital material for training computer programs. This is because sign languages aren't the same everywhere, and they differ between regions, communities, and people. Also, it's tricky to record and explain sign languages. You need special tools like cameras, sensors, and gloves, plus experts who can write down and label the signs, facial expressions, and body movements. So, we really need more efforts to collect and explain data, and find ways to share it. This will help make better computer programs for sign languages.

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2 Modality complexity

Another challenge in creating computational linguistics applications for sign languages is the complexity of the visual-spatial modality. Unlike spoken and written languages, which use linear sequences of sounds or symbols, sign languages use multiple channels of information, such as hand shapes, locations, movements, orientations, eye gaze, facial expressions, and body posture. These channels can convey different meanings, such as grammatical functions, semantic roles, discourse markers, and pragmatic cues. Moreover, these channels can interact with each other, creating complex patterns of coarticulation, modulation, and iconicity. Therefore, there is a need for more sophisticated models and techniques that can capture and analyze the multimodal and nonlinear nature of sign languages, and that can handle the variability and ambiguity that arise from the visual-spatial modality.

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3 Application diversity

A third challenge in creating computational linguistics applications for sign languages is the diversity of the potential applications. Sign languages can be used for various purposes, such as education, entertainment, accessibility, and communication. Each of these purposes may require different types of applications, such as sign language recognition, translation, synthesis, tutoring, captioning, and animation. Each of these applications may also have different requirements, such as speed, accuracy, naturalness, adaptability, and usability. Therefore, there is a need for more research and development that can address the specific needs and challenges of different sign language applications, and that can evaluate their performance and impact on the sign language users and communities.

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4 Ethical issues

A final challenge in creating computational linguistics applications for sign languages is the ethical issues that may arise from the use and misuse of these applications. Sign languages are not only linguistic systems, but also cultural and social identities of the deaf and hard-of-hearing people who use them. Therefore, any computational linguistics application that involves sign languages should respect and protect the rights, interests, and values of the sign language users and communities, and should not harm or exploit them. Moreover, any computational linguistics application that involves sign languages should be developed and implemented with the participation and consultation of the sign language users and communities, and should be accessible and affordable to them. Therefore, there is a need for more ethical awareness and responsibility among the researchers and developers of computational linguistics applications for sign languages, and for more guidelines and regulations that can ensure the ethical and fair use of these applications.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the biggest challenges in creating computational linguistics applications for sign languages?

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1 Data scarcity

2 Modality complexity

3 Application diversity

4 Ethical issues

5 Here’s what else to consider

Linguistics

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