arXiv:2604.26136v2 Announce Type: replace-cross Abstract: Preserving a speaker's voice identity while generating speech in a different language remains a fundamental challenge in spoken language technology, particularly in specialized domains such as scientific communication. In this paper, we address this challenge through our system submission to the International Conference on Spoken Language Translation (IWSLT 2026), the Cross-Lingual Voice Cloning shared task. First, we evaluate several state-of-the-art voice cloning models for cross-lingual speech generation of scientific texts in Arabic
The proliferation of advanced AI models for speech synthesis and translation is making cross-lingual voice cloning technically feasible and increasingly sophisticated.
This technology enables seamless communication and content creation across language barriers while preserving individual identity, which has significant implications for global media, education, and diplomatic relations.
The ability to generate scientific speech in multiple languages with a single speaker's voice dramatically reduces the barriers to global dissemination of specialized knowledge.
- · AI-driven content platforms
- · Science communicators
- · International organizations
- · Speech technology companies
- · Traditional translation agencies
- · Voice actors (for certain tasks)
Scientific research becomes more accessible to a global audience, fostering broader collaboration.
This could lead to a reduction in language-based inequalities in access to advanced knowledge and education.
The technology might be misused for deep-fake content, necessitating new verification and authenticity standards for digital speech.
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Read at arXiv cs.CL