sarapapi/hearing2translate
Sep 2025 – Dec 2025
4 Months active
Languages Used
JSONMarkdownPython
Technical Skills
API integrationData ManagementData ProcessingDataset ManagementRepository CleanupScripting
carlosep93
PROFILE
Carlosep93
Carlos worked on the sarapapi/hearing2translate repository, delivering end-to-end dataset processing and evaluation workflows over four months. He developed Python scripts and Jupyter notebooks to convert raw datasets like MUST-SHE and LibriStutter into structured JSONL formats, enabling reproducible machine learning experiments. His work included building analysis toolkits for cross-language evaluation, normalizing metrics, and refining model comparison frameworks. By integrating data curation, Pandas-based processing, and clear documentation, Carlos improved repository maintainability and onboarding. His contributions established robust pipelines for benchmarking and model iteration, demonstrating depth in data engineering and natural language processing while addressing reproducibility and clarity in ML evaluation.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
6
Lines of code
21,619
Activity Months4
Your Network
15 peopleWork History
December 2025
3 Commits • 1 Features
Dec 1, 2025Month: 2025-12. This month concentrated on delivering enhancements to the LibriStutter analysis notebook in the sarapapi/hearing2translate repository. Key outcomes include normalized execution counts, new LibriStutter model entries, updated system names and metrics calculations, and a refined execution flow to improve the accuracy and clarity of evaluation metrics. These changes were implemented through three commits: a43ff5626b0f0967a6823287dbcb879887834448 (libristutter normalization), dd8e270a7c1911cbfafc5d7a5d6c13e5834c9130 (libristutter stats), and c348c1603f6826924f425de54fd5ddee87d3f29c (libristutter analysis).
3 Commits • 1 Features
Dec 1, 2025Month: 2025-12. This month concentrated on delivering enhancements to the LibriStutter analysis notebook in the sarapapi/hearing2translate repository. Key outcomes include normalized execution counts, new LibriStutter model entries, updated system names and metrics calculations, and a refined execution flow to improve the accuracy and clarity of evaluation metrics. These changes were implemented through three commits: a43ff5626b0f0967a6823287dbcb879887834448 (libristutter normalization), dd8e270a7c1911cbfafc5d7a5d6c13e5834c9130 (libristutter stats), and c348c1603f6826924f425de54fd5ddee87d3f29c (libristutter analysis).
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Focused on delivering a structured model evaluation capability for the Libristutter workflow within sarapapi/hearing2translate. Major deliverable: Enhanced Model Evaluation Framework for Libristutter, enabling side-by-side model comparisons, new model names, and updated execution counts to support reproducible, notebook-driven performance assessment. Key commit: e58d4e9601859e7ed34b30e324d64b8f9d566674 ('libristutter comparison') implementing the framework. Major bugs fixed: None reported for this repository this month. Impact: Improves model selection decisions, accelerates iteration, and increases transparency of evaluation results. Technologies/skills demonstrated: Python-based evaluation tooling, notebook integration, Git version control, and extensible model catalog design. Repository: sarapapi/hearing2translate. Next steps: expand model coverage, automate reporting, and integrate with CI for ongoing evaluation.
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Focused on delivering a structured model evaluation capability for the Libristutter workflow within sarapapi/hearing2translate. Major deliverable: Enhanced Model Evaluation Framework for Libristutter, enabling side-by-side model comparisons, new model names, and updated execution counts to support reproducible, notebook-driven performance assessment. Key commit: e58d4e9601859e7ed34b30e324d64b8f9d566674 ('libristutter comparison') implementing the framework. Major bugs fixed: None reported for this repository this month. Impact: Improves model selection decisions, accelerates iteration, and increases transparency of evaluation results. Technologies/skills demonstrated: Python-based evaluation tooling, notebook integration, Git version control, and extensible model catalog design. Repository: sarapapi/hearing2translate. Next steps: expand model coverage, automate reporting, and integrate with CI for ongoing evaluation.
October 2025
8 Commits • 2 Features
Oct 1, 2025October 2025 (2025-10) delivered end-to-end Libristutter dataset capabilities and cross-language evaluation tooling for sarapapi/hearing2translate. Implemented a reproducible dataset manifest, processing pipeline, and JSONL samples; enriched dataset structure and language-pair entries; and provided a comprehensive README with usage, statistics, and citation guidance. Introduced an analysis toolkit with a notebook, metrics-differences computation, and a new model integration to support evaluation across language pairs. Fixed a path-resolution issue to ensure robust asset access. These efforts establish a reliable benchmarking and model-iteration pipeline, improve onboarding and documentation, and enable clearer business value demonstration.
8 Commits • 2 Features
Oct 1, 2025October 2025 (2025-10) delivered end-to-end Libristutter dataset capabilities and cross-language evaluation tooling for sarapapi/hearing2translate. Implemented a reproducible dataset manifest, processing pipeline, and JSONL samples; enriched dataset structure and language-pair entries; and provided a comprehensive README with usage, statistics, and citation guidance. Introduced an analysis toolkit with a notebook, metrics-differences computation, and a new model integration to support evaluation across language pairs. Fixed a path-resolution issue to ensure robust asset access. These efforts establish a reliable benchmarking and model-iteration pipeline, improve onboarding and documentation, and enable clearer business value demonstration.
October 2025
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025: Delivered data preparation for ML workflows and improved repo hygiene. Features: dataset processing script to convert MUST-SHE data to JSONL with README and sample data files (commits 31d331b47c4f464af2f256f726925ea5f4257165; f555df3cc1fd0e7e342d63b091a3860533ff8ff2). Cleanup: removed MUST-SHE dataset and all related JSONL files to reduce data debt (commit 67357163e30e289a617f201378252630e97e51b2). Impact: Enables reproducible ML experiments, reduces repository bloat, and improves maintainability. Skills demonstrated: Python scripting, data formatting (JSONL), documentation, and Git version control.
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025: Delivered data preparation for ML workflows and improved repo hygiene. Features: dataset processing script to convert MUST-SHE data to JSONL with README and sample data files (commits 31d331b47c4f464af2f256f726925ea5f4257165; f555df3cc1fd0e7e342d63b091a3860533ff8ff2). Cleanup: removed MUST-SHE dataset and all related JSONL files to reduce data debt (commit 67357163e30e289a617f201378252630e97e51b2). Impact: Enables reproducible ML experiments, reduces repository bloat, and improves maintainability. Skills demonstrated: Python scripting, data formatting (JSONL), documentation, and Git version control.
Activity
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Quality Metrics
Correctness89.4%
Maintainability88.0%
Architecture88.0%
Performance88.0%
AI Usage30.8%
Skills & Technologies
Programming Languages
JSONMarkdownPython
Technical Skills
API integrationData AnalysisData CurationData EngineeringData ManagementData ProcessingDataset ManagementDataset ProcessingDocumentationHugging Face DatasetsJupyter NotebookNatural Language ProcessingPandasPythonPython programming
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