{"id":27438361,"url":"https://github.com/coderpat/muda","last_synced_at":"2025-10-04T00:42:59.278Z","repository":{"id":168691396,"uuid":"538683530","full_name":"CoderPat/MuDA","owner":"CoderPat","description":null,"archived":false,"fork":false,"pushed_at":"2024-05-20T20:34:47.000Z","size":224,"stargazers_count":9,"open_issues_count":7,"forks_count":6,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-04-14T20:44:32.615Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CoderPat.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2022-09-19T20:22:38.000Z","updated_at":"2024-11-13T07:33:24.000Z","dependencies_parsed_at":null,"dependency_job_id":"fbcfcd85-46f3-4038-90ab-7115c59349a4","html_url":"https://github.com/CoderPat/MuDA","commit_stats":null,"previous_names":["coderpat/muda"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/CoderPat/MuDA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoderPat%2FMuDA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoderPat%2FMuDA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoderPat%2FMuDA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoderPat%2FMuDA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CoderPat","download_url":"https://codeload.github.com/CoderPat/MuDA/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoderPat%2FMuDA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278250079,"owners_count":25955839,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-03T02:00:06.070Z","response_time":53,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-04-14T20:35:18.727Z","updated_at":"2025-10-04T00:42:59.262Z","avatar_url":"https://github.com/CoderPat.png","language":"Python","readme":"# Multilingual Discourse-Aware (MuDA) Benchmark\n\nThe Multilingual Discourse-Aware (MuDA) Benchmark is a comprehensive suite of taggers and evaluators aimed at advancing the field of context-aware Machine Translation (MT). \n\nTraditional translation quality metrics output uninterpertable scores, and fail to accuratly measure performance on context-aware discourse phenomena. MuDA takes a different direction, relying on neural-based syntatical and morphalogical analysers to measure performance of translation models on specific words and discourse phenomena.\n\nThe MuDA taggers currently support 14 language pairs (see [this directory](CoderPat/MuDA/muda/langs)) but easily supports adding new languages.\n\n## Installation\n\nThe tagger relies on Pytorch (`\u003c1.10`) to run models. If you want to run these models, first install Pytorch. You can find instructions for your system [here](https://pytorch.org/get-started/locally/).\n\nFor example, to install PyTorch on a Linux system with CUDA support in a conda environment, run:\n\n```bash\nconda install pytorch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1 cudatoolkit=11.3 -c pytorch -c conda-forge\n```\n\nThen, to install the rest of the dependencies, run:\n\n```bash\npip install -r requirements.txt\n```\n\n## Example Usage\n\nTo tag an existing dataset, and extract the tags for later use, run the following command. \n\n```bash\npython muda/main.py \\\n    --src /path/to/src \\\n    --tgt /path/to/tgt \\\n    --docids /path/to/docids \\\n    --dump-tags /tmp/maia_ende.tags \\\n    --tgt-lang \"$lang\" \\\n```\n\nTo evaluate models on particular dataset (reporting per-tag metrics such as precision \u0026 recall), run\n\n```bash\npython muda/main.py \\\n    --src /path/to/src \\\n    --tgt /path/to/tgt \\\n    --docids /path/to/docids \\\n    --hyps /path/to/hyps.m1 /path/to/hyps.m2 \\\n    --tgt-lang \"$lang\"\n```\n\nNote that MuDA relies on an `docids` file, containing the same number of lines as the `src/tgt` files and where each line contains a *document id* to which the source/target in the line belong to.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderpat%2Fmuda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcoderpat%2Fmuda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderpat%2Fmuda/lists"}