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sangeet2020/Cross-lingual-topic-identification-in-low-resource-scenarios

Domain:

natural language processing
Creator:
san
Host:
Topic prediction for low-resource language # Cross-lingual topic identification in low resource scenarios The objective is to develop systems for cross-lingual topic ID without relying on machine translation systems and bilingual word embeddings. In other words, given parallel text between a source (eg. English) and target language, and some set of topic labeled documents in a source language, the goal is to predict topic labels for test documents from the target language. ## System block diagram ## Important Note This project is still in the development phase. NOT all codes can be made public at this stage. ## Requirements * Python >= 3.7 * scipy >= 1.3 * numpy >= 1.16.4 * scikit-learn >= 0.21.2 ## Language packs used Kinyarwanda (IL9) Sinhalese (IL10) Zulu Hindi ## Dataset for training English classifier LDC Leidos ## Steps in brief 1. Pre-Processing ``` python src/XML_parser_Universal.py --help ``` 2. Baseline classification on labeled English data 3. Feature representation ``` python src/extract_features_for_test_data.py --help ``` 4. Feature transformation from source language space to the target language (English) space 5. Training English classifier ``` python src/train_classifier_on_eng_sf_features.py --help ``` Training English classifier batch-wise ``` python src/train_clf_batchwise.py --help ``` 6. Predict labels/topics 7. Evaluate average precision score ## Usage - wrapper files ### 1. Pre-processing bash wrapper_preProcess.sh Task performed: * Generate ground truth annotations * Preparing ground truth of the annotations * Convert ASR outputs to a text file and document id file * Analyze English labeled text data * Eliminate out-of-domain docs ### 2. Baseline classification using theme-specific tokens bash wrapper_baseline_best_vocabs.sh Task performed: * Generate the best vocabulary from each class of labeled English text data * Finds the best alpha for each topic/label * Generates bash file to generate features for parallel text * Generates bash file to compute final …

Visit

github.com

Tasks

text classificationtopic classification

Languages

Kinyarwanda

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