Search Results for "level set methods"

Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep...

...It provides an API and tools for (inverted) indexing, storage and retrieval of large amounts of text, with (XML-based) handling of meta-data, tools for text categorisation, including, functionality for XML parsing, term set reduction (and basic keyword extraction), probabilistic classifier induction, sample classification tools, and evaluation modules, a suite of corpus management, curation and distributed access tools. If you use the tool please consider referencing it using the following article: Luz, S., & Sheehan, S. (2020). Methods and visualization tools for the analysis of medical, political and scientific concepts in Genealogies of Knowledge. ...

LexiFinder is a tool to generate analytic indexes from documents automatically. Given one or more source documents and a set of keywords, it extracts all nouns, compares them semantically to the keywords using a pretrained NLP model, and produces a structured, hierarchical index ready to be included in a book or manuscript. LexiFinder works in two ways: as a command-line tool for scripting, automation, and batch processing, and as a graphical application for a guided, point-and-click...

...The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems.

This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). ...

See TTS demo at: http://rslp.racai.ro/index.php?page=tts This is an entirely written in JAVA project which includes a set of tools and methods designed to enable Multilingual Text-to-Speech (TTS) synthesis. We currently support English and Romanian but we will soon train more models and make them available for download. If you want to read more about our other NLP and TTS tools check out http://nlptools.racai.ro.