Stella Bullo · Applied Linguist & Language-Tech Developer (EN/ES)
Case studies, articles, and research-to-prototype work in English and Spanish.
What I do
I work on the language layer of AI systems and datasets. My focus is on annotation and evaluation design, semantic modelling, and building interpretable language systems for multilingual speech and text (EN/ES).
Available for AI training, annotation QA, and language system design (EN/ES). If you need someone to strengthen the language layer of your dataset, evaluation pipeline, or product, let’s talk .
Annotation & Evaluation (EN/ES)
I design annotation schemas, guidelines, prompts, and QA frameworks for multilingual speech and text datasets, ensuring clarity, consistency, and high-quality training data.
Semantic Modelling & Language Systems
I model how people express meaning, emotion, and evaluation, and translate those linguistic frameworks into structured, interpretable systems implemented in annotation pipelines and digital products.
Applied Language Systems
Selected work demonstrating how semantic modelling, annotation design, and evaluation frameworks are implemented in structured, interpretable language systems.
Featured system
A linguistically grounded, rule-based application that translates metaphorical and literal pain descriptions into structured summaries. Built with Flask, YAML taxonomies, and a transparent interpretive framework.
MVP · Live prototype
Modelling framework
Taxonomy design and conceptual modelling that structure how experience, emotion, and evaluation are encoded in language. This framework underpins Explain My Pain and future systems.
Read overviewProfessional practice
Articles and applied work on multilingual annotation design, speech verification, schema development, and evaluation QA for AI training datasets.
Browse articlesStory
I’m a trained linguist with a PhD in Applied Linguistics and 15 years of academic research experience in the UK. My work drew on corpus tools, categorisation, and systematic interpretation, using real-world language data to build analytical frameworks that made patterns of meaning visible and testable.
After relocating to Argentina, I transitioned into applied language engineering. Today I work with annotation frameworks and evaluation processes, and design rule-based systems that support reliable AI training data and interpretable digital products (EN/ES).
Feel free to explore my case studies and writingcovering applied language systems, my research foundations, and reflections on language in everyday life.