The VOXReality project has launched its new Project Results Catalogue, an online collection now available on the project’s website: https://voxreality.eu/project-results/. This catalogue highlights the project’s advancements and contributions to voice interaction in XR.
This comprehensive catalogue features three main types of results: AI Tools for practical use, Scientific Publications sharing research findings, and Public Deliverables.
What You’ll Find in the Catalogue
AI Tools
The “AI Tools” section of the catalogue offers various AI models, datasets and integrations developed by VOXReality. These tools are designed to make voice interaction in XR spaces more natural and responsive to human speech. They cover several key areas:
- Understanding Language: Tools like T5 NLU, intent_recognition, Dialogue System, and navqa help AI understand and respond to human language and intentions within XR environments.
- Multiple Languages: Tools such as Multilingual Translation and whisper-small-el-finetune help remove language barriers in XR, making it accessible worldwide.
- Combining Vision and Language: Tools like Vision and Language Models, video-language_cap, and rgb_language_vqa demonstrate the project’s work in developing AI that understands both visual and spoken information simultaneously in XR. This is crucial for AI to interpret context from what a user says and what they see in the virtual or augmented world, leading to more natural interactions.
- Core Integrations and Performance: Tools such as VOXReality Integration and Model Training and Inference Optimization provide frameworks and optimized solutions for smooth XR development.
Scientific Publications
The “Scientific Publications” section lists academic papers and research findings from the project’s partners. These publications detail the methods, analyses, and progress made in improving XR use cases with machine learning and combining language and vision AI models for immersive XR experiences. Examples of publication topics include:
- XR Improvement & Machine Learning: Papers like “User centric Requirements for Enhancing XR Use Cases with Machine Learning Capabilities” focus on integrating machine learning into practical XR applications and understanding user needs.
- Context-Aware Machine Translation: Research such as “Analyzing the Attention Heads for Pronoun Disambiguation in Context-aware Machine Translation Models” addresses language challenges important for smooth voice interaction, helping AI understand language context and manage conversations in XR environments.
- Multimodal AI & Dialogue Systems: Publications like “Intent-calibrated Self-training for Answer Selection in Open-domain Dialogues” and project overviews “VOXReality: Voice driven interaction in XR spaces” show the project’s broad approach to AI for XR.
Public Deliverables
The “Public Deliverables” section provides access to key documents that outline the project’s progress and specific outcomes. These official reports offer detailed insights into various aspects of the VOXReality project’s development and findings, ensuring transparency.
Driving Progress in XR
The VOXReality Project Results Catalogue serves as a central hub for the project’s outputs, clearly demonstrating its progress and contributions to voice interaction in XR. It is designed for researchers, developers, and the general public to explore the AI tools, scientific knowledge, and public deliverables.
This open access helps speed up innovation by allowing others to build on VOXReality’s work, reducing duplicated efforts and accelerating XR development. This fosters a collaborative environment where knowledge and resources are shared, which is important for quick technological advancement and broad societal impact.
The VOXReality project invites everyone interested to visit the new Project Results Catalogue at https://voxreality.eu/project-results/. Explore the available resources, use the AI tools for your projects, and read the scientific publications and public deliverables for more details on the future of voice-driven XR.
