limco: a linguistic measure collection
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Updated
Jul 8, 2024 - Python
limco: a linguistic measure collection
A visuallization for cognates in various languages and how they spread
Code related to the LREC-COLING 2024 paper "Estimating Lexical Complexity from Document-Level Distributions"
Python library for extracting quantitative, reproducible metrics of multi-level alignment between two speakers in naturalistic language corpora.
Linguistic Field Data Management and Analysis System [LiFE]
Measuring linguistic complexity through information theory
Code, analyses, and data for 'A Linguistic Comparison between Human and ChatGPT-Generated Conversations'
Introducing an English reading assistant—a web application using NLP to enhance understanding of English documents. It allows users to upload English PDFs, employing NLP to highlight recurring words and their definitions.
A Python library that allows easy extraction of a variety of text units within texts...
Lexical & semantic analysis of the CF Conventions Standard Names
How readable is your text? Provide a text input and get its grade level. Scientifically validated.
This is the code and data used to produce the results from the EMNLP 2023 paper Addressing Linguistic Bias through a Contrastive Analysis of Academic Writing in the NLP Domain.
This repo contains a Python script called get_linguistic_features.py - an information extraction script which performs part-of-speech (PoS) tagging and named-entity recognition (NER).
😸 💬 A module to compute textual lexical richness (aka lexical diversity).
Tujtradukilo el Esperanto al Arkaikam Esperantom
A reddit scrapper investigating how redditors pronounce SQL
For a human-centered data science assignment, I analyzed how Google's Perspective API tool detects and categorizes Black language data, also known as AAVE (African-American Vernacular English), from Twitter.
[EMNLP 2021] LingFeat - A Comprehensive Linguistic Features Extraction ToolKit for Readability Assessment
Web application for first person singular pronoun analysis. It follows the depression theory.
Keras-based python framework to compute phonological posterior probabilities from audio files
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