{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Normalizes and denormalizes text in Chinese, English, and Japanese using finite state transducers, converting between written and spoken forms with support for character conversions and linguistic preprocessing.","skillfed_tags":["multilingual-nlp","fst-based","speech-processing"],"use_cases":["Prepare speech recognition output (spoken form) into written text for downstream NLP tasks","Convert written numbers and currency in documents into their spoken equivalents for text-to-speech systems","Preprocess multilingual user input by normalizing punctuation, removing interjections, and converting character widths","Generate multiple candidate normalizations ranked by FST weight for ambiguous text sequences","Build pipelines that require bidirectional text normalization for Chinese, English, or Japanese corpora"],"what_it_does":"WeText is a Python runtime for multilingual text normalization and inverse text normalization using finite state transducers. It converts between written and spoken forms of text\u2014for example, turning \"$12.50\" into \"twelve point five dollars\" or vice versa\u2014across Chinese, English, and Japanese. The package does not depend on Pynini, instead using kaldifst for FST operations.\n\nBeyond basic normalization, it offers character conversions (traditional to simplified Chinese, full-width to half-width), linguistic preprocessing (interjection and punctuation removal, out-of-vocabulary tagging), and language-specific features like erhua removal for Chinese and 0-to-9 conversion for ITN. It exposes both a Python API with support for n-best candidates and exact token mappings, and a command-line interface for quick text processing.","worth_installing":"Yes. The package is actively maintained, has low install friction, carries a permissive license, and fills a specific need for multilingual text normalization with FST-based precision. It is suitable for production use in speech processing, NLP preprocessing, and text-to-speech pipelines. No known vulnerabilities."},"id":"wetext","links":{"html":"https://skillfed.io/packages/wetext","md":"https://skillfed.io/packages/wetext.md","pypi":"https://pypi.org/project/wetext/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-29","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"wetext","python_support":"supports_current","summary":"WeTextProcessing Runtime"},"popularity":{"monthly_downloads":281375,"position":8100,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.6"}