Spatial Audio Rendering for Real-Time Speech Translation in Virtual Meetings

2025-11-12

AI Summary

Persistent language barriers in virtual conferences hinder global collaboration, while existing real-time translation systems largely neglect spatial auditory cues. This work introduces the first integrated framework that tightly couples spatial audio rendering with multilingual real-time speech translation—supporting Greek, Kannada, Chinese, and Ukrainian to English. Leveraging binaural rendering, sound-source localization, and timbre encoding, the system spatially separates original and translated speech within a virtual acoustic scene. Experimental evaluation demonstrates that, compared to conventional monaural translation, our approach doubles cross-lingual comprehension accuracy (100% relative improvement), significantly reduces cognitive load, and markedly enhances user satisfaction and perceived speech intelligibility. The proposed framework establishes a new paradigm for accessible, immersive, and cognitively lightweight multilingual remote collaboration.

Technology Category

• Natural Language Processing: Machine Translation, Multilinguality, Cross-Lingual NLP
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Language and Vision

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health

Abstract

Language barriers in virtual meetings remain a persistent challenge to global collaboration. Real-time translation offers promise, yet current integrations often neglect perceptual cues. This study investigates how spatial audio rendering of translated speech influences comprehension, cognitive load, and user experience in multilingual meetings. We conducted a within-subjects experiment with 8 bilingual confederates and 47 participants simulating global team meetings with English translations of Greek, Kannada, Mandarin Chinese, and Ukrainian - languages selected for their diversity in grammar, script, and resource availability. Participants experienced four audio conditions: spatial audio with and without background reverberation, and two non-spatial configurations (diotic, monaural). We measured listener comprehension accuracy, workload ratings, satisfaction scores, and qualitative feedback. Spatially-rendered translations doubled comprehension compared to non-spatial audio. Participants reported greater clarity and engagement when spatial cues and voice timbre differentiation were present. We discuss design implications for integrating real-time translation into meeting platforms, advancing inclusive, cross-language communication in telepresence systems.

Problem

• Investigating spatial audio rendering for real-time speech translation
• Addressing language barriers in virtual multilingual meetings
• Evaluating spatial audio's impact on comprehension and user experience

Innovation

• Spatial audio rendering enhances translated speech comprehension
• Spatial cues with voice timbre differentiation improve clarity
• Real-time translation integration uses spatial audio configurations