i18n Internationalization
From Spanish localization to the guidelines that shaped wearable AI across languages
Authored the localization guidelines for voice interactions on Meta's wearable devices, starting with Spanish. These guidelines scaled across the ecosystem, shaped ML models, and led to me joining the Translations team.
A global assistant that understands everyone and fosters equitable participation in the future of technology.
Native expertise as a design advantage
Localization isn't translation. As a native Spanish speaker, I defined what "natural" sounds like in a non-English voice experience, adapting interaction patterns, tone, and cultural context across Meta Portal and Ray-Ban Meta.
Adapted phrasing structures, formality levels, and conversational rhythms, not just words.
The assistant had to feel like it belongs in the user's language, not like a translated English experience.
Training translators on conversation design
English designs went through an automatic pipeline to third-party translators who had no conversation design context. Translations lost their conversational quality, making voice interactions feel unnatural in other languages. I trained translators on CxD guidelines, significantly improving quality and supporting English feature parity across global markets.
No conversation design context. Translated strings felt stiff and unnatural.
Translators trained on CxD guidelines. Quality improved significantly, supporting feature parity.
Improving the review process
The review process was slow, requiring multiple steps and links to request a single change. I streamlined the pipeline so designers could review and request changes faster.
Used an internal tool to hear TTS output on Ray-Ban Meta, critical for evaluating if translations sounded natural when spoken aloud.
Simplified the multi-step process so designers could review and request changes in fewer steps.
Shaping how models learn language
As the team shifted to model-based systems, these guidelines became essential for training and evaluating ML models. Collaborated closely with linguists, PMs, and ML engineers to ensure models reflected the same quality as hand-crafted flows.
Co-drove localization initiatives, combining design expertise with linguistic precision.
Guidelines became training data and evaluation criteria for model-based voice interactions.
Aligned localization quality with product goals and language expansion timelines.
Guidelines scaled from Spanish to every language across Meta's wearable ecosystem, shaping both human-designed flows and ML models. This i18n expertise led to joining the Translations team, where I applied those learnings to design live translation on Ray-Ban Meta.