Charibeth Cheng
Chari Cheng is the Associate Dean and a professor at the College of Computer Studies, De La
Salle University. A local pioneer in her field, she co-founded Senti AI and is a recognized expert
in Natural Language Processing (NLP). Since 2003, her work has been driven by a passion for
the digitization and better representation of Philippine languages.
Her contributions to the field have been widely recognized. She contributed to a 2020 Asian
Development Bank project that developed NLP tools for monitoring the Sustainable
Development Goals (SDGs). For her work on multilingual machine translation, she received the
2024 Imminent Research Grant from Translated, Inc., as the only Asian recipient that year. This
year, she received 2 grants from Google to support her team’s work on the development of the
models for Philippine languages.
Beyond academia, Chari is an active consultant on AI system design, evaluation, and impact
assessment. She is also a strong advocate for community collaboration, regularly sharing her
team’s resources through talks and open repositories to support the broader NLP community.
Session
As Large Language Models (LLMs) expand into global markets, they often hit a "Nuance Gap" or a failure to distinguish literal meaning from cultural context. This presentation examines the technical hurdles of building culturally competent AI through two lenses, namely, linguistic ambiguity (sarcasm) and localized safety (toxicity). Using the Philippines as a case study, we identify four critical hurdles: (1) the Linguistic Inversion Problem, where sarcasm flips intended sentiment; (2) the Context Vacuum, where text lacks the "cultural scaffolding" necessary for interpretation; (3) the Data Desert of low-resource languages; and (4) the Western-Centricity of standard safety filters. We propose a roadmap for researchers to move beyond literal translation toward AI that respects the "unspoken" and "unseen" nuances of regional identities.