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Hunspell Dict KoKorean spellchecking dictionary for Hunspell
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Deeptoxictop 1% solution to toxic comment classification challenge on Kaggle.
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SolrtexttaggerA text tagger based on Lucene / Solr, using FST technology
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Nlp4rec PapersPaper list of NLP for recommender systems
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Nlp profilerA simple NLP library allows profiling datasets with one or more text columns. When given a dataset and a column name containing text data, NLP Profiler will return either high-level insights or low-level/granular statistical information about the text in that column.
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LazynlpLibrary to scrape and clean web pages to create massive datasets.
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UdpipeR package for Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing Based on the UDPipe Natural Language Processing Toolkit
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Displacy Ent💥 displaCy-ent.js: An open-source named entity visualiser for the modern web
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Deep Survey Text ClassificationThe project surveys 16+ Natural Language Processing (NLP) research papers that propose novel Deep Neural Network Models for Text Classification, based on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). It also implements each of the models using Tensorflow and Keras.
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GerbilGERBIL - General Entity annotatoR Benchmark
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Covid Papers BrowserBrowse Covid-19 & SARS-CoV-2 Scientific Papers with Transformers 🦠 📖
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Ngx Dynamic Dashboard FrameworkThis is a JSON driven angular x based dashboard framework that is inspired by JIRA's dashboard implementation and https://github.com/raulgomis/angular-dashboard-framework
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StopwordsDefault English stopword lists from many different sources
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Nlp bahasa resourcesA Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia
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MixtextMixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
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Bert Vocab BuilderBuilds wordpiece(subword) vocabulary compatible for Google Research's BERT
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Cookiecutter Spacy FastapiCookiecutter API for creating Custom Skills for Azure Search using Python and Docker
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Pytorch NlpBasic Utilities for PyTorch Natural Language Processing (NLP)
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Mtbook《机器翻译:基础与模型》肖桐 朱靖波 著 - Machine Translation: Foundations and Models
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NlprePython library for Natural Language Preprocessing (NLPre)
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NlvrCornell NLVR and NLVR2 are natural language grounding datasets. Each example shows a visual input and a sentence describing it, and is annotated with the truth-value of the sentence.
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DelbotIt understands your voice commands, searches news and knowledge sources, and summarizes and reads out content to you.
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KashgariKashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
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GensimTopic Modelling for Humans
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Awesome Nlp📖 A curated list of resources dedicated to Natural Language Processing (NLP)
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NelEntity linking framework
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SlingSLING - A natural language frame semantics parser
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Visdial RlPyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning
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CleannlpR package providing annotators and a normalized data model for natural language processing
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Speech signal processing and classificationFront-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
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SwagafRepository for paper "SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference"
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DostoevskySentiment analysis library for russian language
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NeuralqaNeuralQA: A Usable Library for Question Answering on Large Datasets with BERT
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FoxFederated Knowledge Extraction Framework
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Sequence taggingNamed Entity Recognition (LSTM + CRF) - Tensorflow
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G2pcg2pC: A Context-aware Grapheme-to-Phoneme Conversion module for Chinese
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Deep Math Machine Learning.aiA blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
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PythonrougePython wrapper for evaluating summarization quality by ROUGE package
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ParallaxTool for interactive embeddings visualization
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PhrasalA large-scale statistical machine translation system written in Java.
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GladGlobal-Locally Self-Attentive Dialogue State Tracker
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QbQANTA Quiz Bowl AI
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