sarapapi/hearing2translate
Aug 2025 – Dec 2025
5 Months active
Languages Used
PythonBashJSONMarkdownShell
Technical Skills
Data EngineeringData ProcessingDataset ManagementPythonPython ScriptingScripting
Jorge Iranzo
PROFILE
Jorge Iranzo
Worked on the sarapapi/hearing2translate repository, building and refining multilingual speech and translation data pipelines. Developed Python scripts and Jupyter notebooks to automate dataset integration, standardize manifest handling, and streamline evaluation workflows across datasets like CS-FLEURS, Europarl-ST, and Neuroparl-ST. Enhanced data reliability and reproducibility by modularizing JSON schema management and introducing dotenv-based environment configuration. Implemented length-aware inference using Librosa for improved transcription accuracy and expanded support for noisy data evaluation. Consolidated translation metrics analysis with CSV processing and visualization, enabling data-driven insights. Demonstrated expertise in Python scripting, data engineering, and natural language processing to accelerate model development and benchmarking.
Overall Statistics
Feature vs Bugs
66%Features
Repository Contributions
32Total
Bugs
10
Commits
32
Features
19
Lines of code
1,072,743
Activity Months5
Your Network
17 peopleWork History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for sarapapi/hearing2translate: Focused on expanding translation evaluation capabilities with a dedicated Translation Metrics Analysis Framework. Delivered new analysis scripts and Jupyter notebooks to combine and process CSV-based translation metrics across multiple datasets, enabling clearer performance visibility and data-driven decision making for model improvements. The work establishes standardized metrics and reproducible evaluation across datasets such as cs-fleurs, europarl, neuroparl, and mexpresso. No major bug fixes were reported this month; activities were primarily feature development and dataset integration. Overall impact includes laying the groundwork for data-driven optimization of translation systems and improved evaluation capabilities. Technologies/skills demonstrated include Python scripting, Jupyter notebooks, CSV data processing, dataset consolidation, and reproducible analytics.
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for sarapapi/hearing2translate: Focused on expanding translation evaluation capabilities with a dedicated Translation Metrics Analysis Framework. Delivered new analysis scripts and Jupyter notebooks to combine and process CSV-based translation metrics across multiple datasets, enabling clearer performance visibility and data-driven decision making for model improvements. The work establishes standardized metrics and reproducible evaluation across datasets such as cs-fleurs, europarl, neuroparl, and mexpresso. No major bug fixes were reported this month; activities were primarily feature development and dataset integration. Overall impact includes laying the groundwork for data-driven optimization of translation systems and improved evaluation capabilities. Technologies/skills demonstrated include Python scripting, Jupyter notebooks, CSV data processing, dataset consolidation, and reproducible analytics.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025: Delivered a new Evaluation Results Combiner for Europarl and Neuroparl-ST within the hearing2translate repo. This involved adding a script to merge evaluation results and introduce case-insensitive metrics, plus refinements to the output format to improve usability and downstream reporting. The work enhances model analysis capabilities and accelerates benchmarking by providing a unified view of translations across datasets. Key outcomes include clearer performance signals for stakeholders and a repeatable workflow for future dataset integrations.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025: Delivered a new Evaluation Results Combiner for Europarl and Neuroparl-ST within the hearing2translate repo. This involved adding a script to merge evaluation results and introduce case-insensitive metrics, plus refinements to the output format to improve usability and downstream reporting. The work enhances model analysis capabilities and accelerates benchmarking by providing a unified view of translations across datasets. Key outcomes include clearer performance signals for stakeholders and a repeatable workflow for future dataset integrations.
October 2025
4 Commits • 3 Features
Oct 1, 2025In October 2025, delivered feature enhancements, data quality improvements, and evaluation tooling for sarapapi/hearing2translate to boost transcription accuracy, robustness, and visibility of model performance. Key work focused on length-aware inference, dataset integrity, and expansion of noisy-data support with thorough evaluation utilities.
4 Commits • 3 Features
Oct 1, 2025In October 2025, delivered feature enhancements, data quality improvements, and evaluation tooling for sarapapi/hearing2translate to boost transcription accuracy, robustness, and visibility of model performance. Key work focused on length-aware inference, dataset integrity, and expansion of noisy-data support with thorough evaluation utilities.
October 2025
September 2025
23 Commits • 13 Features
Sep 1, 2025This monthly summary highlights the key features shipped, bugs fixed, and the technical accomplishments for Sep 2025 on sarapapi/hearing2translate. The month focused on stabilizing the data-inference pipeline, enabling scalable multilingual support, and improving deployment reliability. Key outcomes include inference readiness for CS-FLEURS, OWSM integration, dotenv-based environment management, MExpresso multilingual expansion, and Europarl-ST stabilization with standardized data paths.
September 2025
23 Commits • 13 Features
Sep 1, 2025This monthly summary highlights the key features shipped, bugs fixed, and the technical accomplishments for Sep 2025 on sarapapi/hearing2translate. The month focused on stabilizing the data-inference pipeline, enabling scalable multilingual support, and improving deployment reliability. Key outcomes include inference readiness for CS-FLEURS, OWSM integration, dotenv-based environment management, MExpresso multilingual expansion, and Europarl-ST stabilization with standardized data paths.
August 2025
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Focused on dataset tooling and stability for the hearing2translate pipeline. Delivered CS-FLEURS dataset integration with a dedicated dataset generation script and standardized manifest handling. Fixed CSFleurs generation by correcting src_ref to emit actual text and modularizing JSON schema handling to simplify imports. These changes improve data reliability, reproducibility, and accelerate downstream model development for multilingual ASR.
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Focused on dataset tooling and stability for the hearing2translate pipeline. Delivered CS-FLEURS dataset integration with a dedicated dataset generation script and standardized manifest handling. Fixed CSFleurs generation by correcting src_ref to emit actual text and modularizing JSON schema handling to simplify imports. These changes improve data reliability, reproducibility, and accelerate downstream model development for multilingual ASR.
August 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability89.4%
Architecture86.2%
Performance85.0%
AI Usage24.4%
Skills & Technologies
Programming Languages
BashJSONMarkdownPythonShell
Technical Skills
Audio ProcessingCSV handlingCSV manipulationConfiguration ManagementData CleaningData EngineeringData HandlingData LoadingData ProcessingData ValidationDataset CurationDataset ManagementDevOpsDocumentationEnvironment Configuration
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