{"repo":"analyticsinmotion/werpy","free":true,"listed":false,"github":"https://github.com/analyticsinmotion/werpy","clone":"git clone https://github.com/analyticsinmotion/werpy.git","description":"🐍📦 Ultra-fast Python package for calculating and analyzing the Word Error Rate (WER). Built for the scalable evaluation of speech and transcription accuracy.","language":"Python","stars":29,"topics":["wer","word-error-rate","python","python-package","nlp","speech-to-text","stt","stt-benchmark","levenshtein-distance","asr"],"license":"BSD-3-Clause","category":"machine-learning","readme_excerpt":"Word Error Rate for Python --- --- Meta          License       Security       Testing          Package          What is werpy? werpy is an ultra-fast, lightweight Python package for calculating and analyzing Word Error Rate (WER) between two sets of text. Built for flexibility and ease of use, it supports multiple input types such as strings, lists, and NumPy arrays. This makes it ideal for everything from quick experiments to large-scale evaluations. With speed in mind at every scale, werpy harnesses the efficiency of C optimizations to accelerate processing, delivering ultra-fast results from small datasets to enterprise-level workloads. It also comes packed with powerful features, including: - 🔤 Built-in text normalization to handle data inconsistencies - ⚙️ Customizable error penalties for insertions, deletions, and substitutions - 📋 A detailed summary output for in-depth error analysis werpy is a quality-focused package, built to production-grade standards for reliability and robustness. Functions available in werpy The following table provides an overview of the functions that can be used in werpy. Function Description ------------- ------------- normalize(text) Preprocess input text to remove punctuation, remove duplicated spaces, leading/trailing blanks and convert all words to lowercase. wer(reference, hypothesis) Calculate the overall W","default_branch":null,"files":null,"tree":[],"storefront":"/r/analyticsinmotion","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/analyticsinmotion/werpy/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}