The main features of fawazahmed0/quran-api are: Natural Language Processing, Developer Tools, Literary Collections, Literature and Reference, Literature and Texts, Books.
Open-source alternatives to fawazahmed0/quran-api include: thundercomb/poetrydb — The Internet's first Poetry API. crossref/rest-api-doc — Documentation for Crossref's REST API. For questions or suggestions, see https://community.crossref.org/. chinese-poetry/chinese-poetry — This project is a comprehensive dataset and archive of classical Chinese poetry, prose, and Confucian classics. It… fedeperin/potterapi — A REST Harry Potter API with images and information about books, characters and spells. Translated to many languages. adam-dev2/library-management-api — Backend specific project. corentinj/real-time-voice-cloning — This project is a neural text-to-speech engine and voice cloning toolkit designed to generate synthetic speech that…
Documentation for Crossref's REST API. For questions or suggestions, see https://community.crossref.org/
This project is a comprehensive dataset and archive of classical Chinese poetry, prose, and Confucian classics. It serves as a digital humanities corpus, providing machine-readable access to hundreds of thousands of poems and detailed poet biographies, specifically spanning the Tang and Song dynasties. The collection is distinguished by its scholarly depth, incorporating textual variation annotations to track disputed characters across different source editions. It also includes tonal pattern mapping to describe the rhythmic and phonetic structures of the verse, alongside a popularity ranking
This project is a neural text-to-speech engine and voice cloning toolkit designed to generate synthetic speech that mimics the vocal characteristics of a target speaker. It functions as a real-time audio synthesizer, utilizing a deep learning pipeline to convert written text into high-fidelity speech output with minimal latency. The system employs a transfer learning framework that leverages pre-trained speaker verification models to adapt synthesis to new, unseen vocal identities. By using an encoder-based speaker embedding process, the toolkit maps variable-length audio samples into a laten
