Over four months, contributed to the sarapapi/hearing2translate repository by building and refining a translation evaluation pipeline supporting ACL and MCIF benchmarks. Developed features for automated CSV processing, cross-language analytics, and reproducible reporting, leveraging Python, Jupyter Notebooks, and LaTeX for data analysis and visualization. Enhanced the workflow with robust data aggregation, notebook-based evaluation, and integration of machine translation systems, while improving repository hygiene and documentation. Addressed bugs in data mapping and analysis calculations, ensuring reliable metrics and maintainability. The work enabled streamlined benchmarking, automated reporting, and easier onboarding, supporting data-driven decisions and consistent evaluation across multiple language pairs and systems.
December 2025 monthly summary for sarapapi/hearing2translate focused on delivering robust reporting, improved cross-language analytics, and clearer translation quality metrics. The work reduced manual reporting steps, standardized cross-language comparisons, and enhanced visibility into translation performance while cleaning up legacy analysis artifacts.
December 2025 monthly summary for sarapapi/hearing2translate focused on delivering robust reporting, improved cross-language analytics, and clearer translation quality metrics. The work reduced manual reporting steps, standardized cross-language comparisons, and enhanced visibility into translation performance while cleaning up legacy analysis artifacts.
Month: 2025-11 — Focused on improving translation evaluation workflow in sarapapi/hearing2translate. Delivered notebook-based data analysis enhancements, corrected data-analysis defects, and refreshed notebook infrastructure and dependencies to enable more reliable benchmarks, faster feature delivery, and better reproducibility for stakeholders. These changes improved data integrity, enabled cross-dataset comparisons, and tightened dependency management for smoother deployments.
Month: 2025-11 — Focused on improving translation evaluation workflow in sarapapi/hearing2translate. Delivered notebook-based data analysis enhancements, corrected data-analysis defects, and refreshed notebook infrastructure and dependencies to enable more reliable benchmarks, faster feature delivery, and better reproducibility for stakeholders. These changes improved data integrity, enabled cross-dataset comparisons, and tightened dependency management for smoother deployments.
In October 2025, delivered an end-to-end evaluation toolkit for ACL/MCIF benchmarks within the hearing2translate project. The work established notebooks and CSV-based difference analysis, enabling structured scoring and cross-inference across systems and language pairs. This setup supports data-driven benchmarking, performance tracking, and quick insight generation for product decisions.
In October 2025, delivered an end-to-end evaluation toolkit for ACL/MCIF benchmarks within the hearing2translate project. The work established notebooks and CSV-based difference analysis, enabling structured scoring and cross-inference across systems and language pairs. This setup supports data-driven benchmarking, performance tracking, and quick insight generation for product decisions.
September 2025 (sarapapi/hearing2translate) focused on stabilizing core ACL workflow, expanding translation coverage, and improving maintainability. Key features delivered include ACL 60/60 final revision, EdAcc: path and doc_id revision, long-form manifests, separate long and short forms, ELITR integration, and language/MCIF enhancements, plus documentation updates and repository hygiene improvements. Major bugs fixed include long-form mapping, readme issues, and ACL partial removal. These efforts yield a more reliable translation pipeline with broader language support, reproducible evaluation, and easier onboarding for contributors. Technologies demonstrated include git-driven incremental delivery, ELITR/MT pipeline integration, MCIF support, comprehensive documentation, and robust repository hygiene.
September 2025 (sarapapi/hearing2translate) focused on stabilizing core ACL workflow, expanding translation coverage, and improving maintainability. Key features delivered include ACL 60/60 final revision, EdAcc: path and doc_id revision, long-form manifests, separate long and short forms, ELITR integration, and language/MCIF enhancements, plus documentation updates and repository hygiene improvements. Major bugs fixed include long-form mapping, readme issues, and ACL partial removal. These efforts yield a more reliable translation pipeline with broader language support, reproducible evaluation, and easier onboarding for contributors. Technologies demonstrated include git-driven incremental delivery, ELITR/MT pipeline integration, MCIF support, comprehensive documentation, and robust repository hygiene.
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