{"id":50244858,"url":"https://github.com/srvCodes/mt-dma","last_synced_at":"2026-06-29T20:00:57.543Z","repository":{"id":186276466,"uuid":"157974817","full_name":"srvCodes/mt-dma","owner":"srvCodes","description":null,"archived":false,"fork":false,"pushed_at":"2018-11-17T11:31:47.000Z","size":5838,"stargazers_count":1,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-04-28T15:34:48.850Z","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/srvCodes.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}},"created_at":"2018-11-17T10:44:52.000Z","updated_at":"2019-05-14T12:25:57.000Z","dependencies_parsed_at":null,"dependency_job_id":"44f08071-da46-4eef-bffa-6803871636a8","html_url":"https://github.com/srvCodes/mt-dma","commit_stats":null,"previous_names":["srvcodes/mt-dma"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/srvCodes/mt-dma","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/srvCodes%2Fmt-dma","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/srvCodes%2Fmt-dma/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/srvCodes%2Fmt-dma/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/srvCodes%2Fmt-dma/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/srvCodes","download_url":"https://codeload.github.com/srvCodes/mt-dma/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/srvCodes%2Fmt-dma/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34941027,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-29T02:00:05.398Z","response_time":58,"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":"2026-05-26T23:00:19.776Z","updated_at":"2026-06-29T20:00:57.538Z","avatar_url":"https://github.com/srvCodes.png","language":"Python","funding_links":[],"categories":["NLP per Language"],"sub_categories":["Libraries and Tooling"],"readme":"# Multi-Task Deep Morphological Analyzer\n\nThis repo contains the code for our paper entitled **Multi Task Deep Morphological Analyzer : Context Aware Neural Joint Morphological Tagging and Lemma Prediction**. The Web API service is accessible [here](http://35.154.251.44/).\n\nA sample analysis:\n\n![sample](https://github.com/Saurav0074/mt-dma/blob/master/hindi/images/sample.png)\n\n## Experiements\n\nBoth the directories follow the organization:\n\n1. [preProcessing](https://github.com/Saurav0074/mt-dma/tree/master/hindi/preProcessing) contains the code for dataset parsing. Datasets can be downloaded from the website of [Universal Dependencies](http://universaldependencies.org/).\n\n2. [dataInfo](https://github.com/Saurav0074/mt-dma/tree/master/hindi/dataInfo) contains details on data set statistics.\n\n3. [Models](https://github.com/Saurav0074/mt-dma/tree/master/hindi/models) for all experiments:\n  - [multiTask_with_context4.py](https://github.com/Saurav0074/mt-dma/blob/master/hindi/models/multiTask_with_context4.py) hosts the fully BiLSTM model for a CW of 4 words.\n  - [multiTask_with_attention.py](https://github.com/Saurav0074/mt-dma/blob/master/hindi/models/multiTask_with_attention.py) hosts the character CNN-RNN based MT-DMA model, as reported in the paper.\n  - [onlyFeatures.py](https://github.com/Saurav0074/mt-dma/blob/master/hindi/models/onlyFeatures.py) and [onlyRoots.py](https://github.com/Saurav0074/mt-dma/blob/master/hindi/models/onlyRoots.py) contain the codes for individual learning.\n  \n4. [Code](https://github.com/Saurav0074/mt-dma/tree/master/hindi/featureOptimization)\n for MOO based GA feature selection.\n \n5. Code for post processing, visualization, BLEU, Levenshtein and word accuracy calculation can be found in [postProcessingAndVisualization](https://github.com/Saurav0074/mt-dma/tree/master/hindi/postProcessingAndVisualization).\n\n5. [Outputs](https://github.com/Saurav0074/mt-dma/tree/master/hindi/outputs) on the HDTB and UDTB datasets.\n\n6. Outputs for [t-SNE plots](https://github.com/Saurav0074/mt-dma/tree/master/hindi/tsnePlots), [GA graphs](https://github.com/Saurav0074/mt-dma/tree/master/hindi/gaGraphs), and [Precision-Recall curves](https://github.com/Saurav0074/mt-dma/tree/master/hindi/prCurves).\n\n# MOO optimization\n\nCubic-spline interpolations for validation accuracies of population:\n\n![images](https://github.com/Saurav0074/mt-dma/blob/master/hindi/images/cubic-splines.png)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FsrvCodes%2Fmt-dma","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FsrvCodes%2Fmt-dma","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FsrvCodes%2Fmt-dma/lists"}