{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Converts spelling to IPA phonetic transcription and measures language similarity across independent axes: phonology, reading, spelling, script, genealogy, time, and geography.","skillfed_tags":["phonetics","multilingual","linguistics"],"use_cases":["Transcribe text to IPA for linguistic research, speech synthesis, or phonetic analysis across hundreds of language varieties.","Measure phonological and orthographic distance between language pairs to study mutual intelligibility or dialect relationships.","Build multilingual text-to-speech systems that need per-language grapheme-to-phoneme rules without training separate models.","Analyze how spelling conventions diverge from pronunciation in a single language or across related languages.","Refine ambiguous transcriptions using custom rescoring rules for domain-specific or specialized phonetic contexts."],"what_it_does":"orthography2ipa is a linguistically motivated library for converting written text to IPA phonetic notation and measuring how languages relate to each other. It ships with data specs for 676 languages and 73 clade nodes covering major language families, reconstructed proto-languages, dialects, and creoles. Rather than learning phoneme-to-sound mappings from weights, the library uses declarative per-language JSON specs that define graphemes, phonemes, allophones, positional rules, and genealogical metadata. A shared, language-agnostic engine applies these specs to produce transcriptions and confidence scores.\n\nThe library's core insight is that language similarity is multidimensional: two languages can sound alike but write differently, or vice versa. It measures each axis independently\u2014phonological inventory overlap, how the same text sounds across languages, how the same sounds are spelled, script typology, ancestry, temporal span, and geographic distance. When spelling is ambiguous, the engine builds a ranked lattice of possible pronunciations with costs, allowing downstream systems to refine choices via custom rescoring rules. It also handles edge cases like logographic scripts (Chinese Hanzi has no grapheme map but a full phonology) and reconstructed languages (Proto-Indo-European declares its phonemes directly).","worth_installing":"Yes, if you need IPA transcription or language similarity metrics for research or NLP. The library is actively maintained, has no known vulnerabilities, and covers a broad language base. The Alpha status and early release history mean the API and data specs may shift; verify transcription accuracy for your specific languages before production use. Low install friction and permissive licensing make it a low-risk addition."},"id":"orthography2ipa","links":{"html":"https://skillfed.io/packages/orthography2ipa","md":"https://skillfed.io/packages/orthography2ipa.md","pypi":"https://pypi.org/project/orthography2ipa/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-16","license_spdx":null,"license_treatment":"permissive","name":"orthography2ipa","python_support":"supports_current","summary":"Linguistically motivated grapheme-to-IPA and allophone mappings for 350+ language codes"},"popularity":{"monthly_downloads":107342,"position":12617,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"7.30.0"}