Sci Simple

New Science Research Articles Everyday

# Computer Science # Computer Vision and Pattern Recognition

Revolutionizing Media Accessibility with Synthetic Signers

New technology creates sign language videos for the Deaf and Hard of Hearing community.

Sudha Krishnamurthy, Vimal Bhat, Abhinav Jain

― 8 min read


Sign Language Tech Sign Language Tech Breakthrough for the DHH community. Creating immersive media experiences
Table of Contents

In today’s world of streaming services, everyone wants to catch the latest shows and movies. But what about the Deaf and Hard of Hearing (DHH) community? They often miss out on the fun because regular Captions or subtitles don't cut it. Enter a new way to make videos more accessible: creating Sign Language videos using Synthetic Signers. This report dives into how technology is being used to create these customizable sign language videos, making media a lot more enjoyable for everyone.

The Challenge of Accessibility

As many streaming platforms continue to grow, so does the variety of content available. Whether it's a gripping movie, a hilarious stand-up comedy show, or even a live concert, viewers from all walks of life can tune in. However, while there have been fantastic improvements in making content available in different languages through dubbing and translation, the same can't be said for the DHH community.

For many in this community, traditional options like closed captions can be limiting. They may struggle with reading or simply prefer the visual expression of sign language. Unfortunately, there aren’t enough trained sign language interpreters to keep up with the surge in media content. This leaves audiences feeling left out, and the need for more expressive alternatives is pressing.

Why Sign Language?

Sign language is more than just hand gestures; it’s a full-fledged visual language. It allows the DHH community to connect with media content in ways that text simply can’t. While captions can provide a basic translation of what's being said, they can miss the tone, emotion, and context that sign language expresses. Think of sign language as a movie with a fantastic plot but lacking special effects—something essential is missing.

From Challenges to Solutions

Recognizing these challenges, tech experts have set out to improve media accessibility for the DHH community by creating sign language videos featuring synthetic signers. With the help of advanced modeling techniques, they can now generate realistic and expressive signers, making videos more engaging.

The Approach

At the heart of this new technology are two key modeling approaches: parametric modeling and generative modeling. Let's break it down!

Parametric Modeling

This approach helps retarget the movements of a human signer to a 3D model. The process starts with taking the movements from a video of a person signing and translating those movements onto a digital avatar. By capturing real-life signing poses, the tech ensures that the synthetic signer looks and moves convincingly.

Generative Modeling

Once the poses are set, generative modeling kicks in to bring the synthetic signer to life. This involves using advanced algorithms that can create new video frames by building on the poses while keeping them visually appealing. The beauty of this method is that it allows for Customization. Viewers can request signers that look a certain way—whether that’s age, gender, or even skin tone—making the videos relatable to a wider audience.

Customization Features

Imagine watching a kids’ show and seeing a signer who looks like a young child! That’s pretty cool. The customization feature caters to different preferences, ensuring that every viewer feels included, no matter their background.

The User Experience

To understand what works best for the audience, a survey conducted with a group of sign language users provided some eye-opening feedback. It turns out that while many users appreciate synthetic signers, they prefer them to be more expressive and lifelike, rather than robotic or stiff.

A Preference for Realism

When shown samples of videos featuring both human signers and synthetic signers, most users leaned towards those that felt more human-like in appearance. No one wants to be entertained by a robot, after all!

The Power of Customization

The survey also showed that users wanted the ability to customize signers to cater to their local community. For instance, a signer who looks like a kid would be more appealing in educational shows for children. Similarly, a signer who reflects the local community's diversity could enhance the viewing experience significantly.

Addressing Various Challenges

Creating these videos isn’t as simple as it sounds. There are several challenges to overcome, but tech experts have made significant progress.

Ensuring High-Fidelity Pose Transfer

Whether you’re dealing with a lighthearted comedy or a serious news segment, the signing needs to be smooth and clear. This means that capturing the essence of each sign as accurately as possible is crucial. High-fidelity transfer ensures that the synthetic signer is interpreted in the same way by everyone, regardless of where they’re watching from.

Customization Without Hassle

Another challenge is making the customization process easy and fast. If users have to spend hours training a model to get their ideal signer, it's less likely they’ll stick with it. The goal here is to create a setup that can adapt quickly to meet different needs without excessive training.

A Peek at the Technology

So, how does all this magic happen? Let’s take a look at the different technological components that come together to create these engaging sign language videos.

MediaPipe Magic

One of the key tools used for pose extraction is MediaPipe. This handy library helps grab the essential poses from a signing video, making it possible to translate them to a synthetic signing avatar. While it’s effective, it sometimes struggles with rapid movements, leaving tech experts to get creative with how they smooth out those poses.

Filtering Out the Jitter

Ever watch a video where the frame jumps around like a kid on a sugar rush? That’s jitter, and it can be distracting. To combat this, a smoothing algorithm is applied to the poses, making sure everything flows smoothly, much like a well-choreographed dance.

Avatar Rendering

After filtering, those poses are then transferred onto a 3D avatar. The avatars are designed to look realistic, complete with textures and lighting that mimic real-life scenarios. Think of it as creating an animated character who can convey emotions and expressions just as well as a human signer.

Generating the Synthetic Signer

The next step is generating a synthetic signer. Here, the appearance and movement of the signer are created separately. By using image prompts and other techniques, this step allows for more diverse and relatable signers. Whether you want a tall, short, or middle-of-the-road signer, the technology can accommodate.

Results and Improvements

The technology has come a long way, but constant evaluations keep it on track. The creators routinely assess the videos for realism and consistency by using various metrics.

Temporal Consistency

One of the essential aspects of creating believable sign language videos is maintaining a consistent appearance of the signer across frames. This means users can rely on the signer looking similar from beginning to end, avoiding any sudden costume changes!

User Feedback

Feedback from users plays a crucial role in improving the technology. The results of the initial surveys have led to enhancements that prioritize realism and customization. After all, if the users aren't happy, then what's the point?

The Fun of Personalization

Imagine you could watch your favorite show with a signer who looks just like you or someone from your community. Thanks to the personalization feature, users can input a single image of a person to guide the creation of the signer they prefer. This makes the entire experience much more relatable.

Using Multimodal Prompts

To further refine the signer's appearance, users can provide multi-faceted prompts. For instance, adding detail about the outfit along with the image can create a more tailored experience. Do you want your signer in a blue shirt and glasses? Just say the word!

Signer Diversity

The beauty of this technology is that it opens the door to a variety of signers who can cater to different audiences. With customizable options available, the goal is to ensure that everyone can enjoy the content in the way that suits them best.

Generating Diverse Signers

Whether it’s a young boy signing a kids’ show or an older woman conveying a heartfelt message, this technology makes it possible to create a range of signers that resonate with various demographics.

Future Prospects

As exciting as these developments are, there’s still much to accomplish. The technology continues to improve, with ongoing research aimed at making the signing experience even better. User evaluations will play a central role in ensuring that innovations align with audience needs.

Real-Life Testing

At some point, testing with real-life users will provide even more insights into how these sign language videos are received by the DHH community. This will lead to improvements that could further enhance accessibility.

Conclusion

Making media content accessible to the DHH community has come a long way, thanks to innovative technology that generates customizable sign language videos. By blending realism, personalization, and effective pose transfer, this technology aims to bridge the gap and include everyone in the joy of shared media experiences.

So kick back, relax, and enjoy the show—because everyone deserves to feel included, no matter how they choose to communicate!

Original Source

Title: DiffSign: AI-Assisted Generation of Customizable Sign Language Videos With Enhanced Realism

Abstract: The proliferation of several streaming services in recent years has now made it possible for a diverse audience across the world to view the same media content, such as movies or TV shows. While translation and dubbing services are being added to make content accessible to the local audience, the support for making content accessible to people with different abilities, such as the Deaf and Hard of Hearing (DHH) community, is still lagging. Our goal is to make media content more accessible to the DHH community by generating sign language videos with synthetic signers that are realistic and expressive. Using the same signer for a given media content that is viewed globally may have limited appeal. Hence, our approach combines parametric modeling and generative modeling to generate realistic-looking synthetic signers and customize their appearance based on user preferences. We first retarget human sign language poses to 3D sign language avatars by optimizing a parametric model. The high-fidelity poses from the rendered avatars are then used to condition the poses of synthetic signers generated using a diffusion-based generative model. The appearance of the synthetic signer is controlled by an image prompt supplied through a visual adapter. Our results show that the sign language videos generated using our approach have better temporal consistency and realism than signing videos generated by a diffusion model conditioned only on text prompts. We also support multimodal prompts to allow users to further customize the appearance of the signer to accommodate diversity (e.g. skin tone, gender). Our approach is also useful for signer anonymization.

Authors: Sudha Krishnamurthy, Vimal Bhat, Abhinav Jain

Last Update: 2024-12-05 00:00:00

Language: English

Source URL: https://arxiv.org/abs/2412.03878

Source PDF: https://arxiv.org/pdf/2412.03878

Licence: https://creativecommons.org/licenses/by-nc-sa/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to arxiv for use of its open access interoperability.

More from authors

Similar Articles