English (India) MFA dictionary v3.1.0#
@techreport{mfa_english_india_mfa_dictionary_2024,
author={McAuliffe, Michael and Sonderegger, Morgan},
title={English (India) MFA dictionary v3.1.0},
address={\url{https://mfa-models.readthedocs.io/pronunciation dictionary/English/English (India) MFA dictionary v3_1_0.html}},
year={2024},
month={Jun},
}
|
Installation#
Install from the MFA command line:
mfa model download dictionary english_india_mfa
Or download from the release page.
The dictionary available from the release page and command line installation has pronunciation and silence probabilities estimated as part acoustic model training (see Silence probability format and training pronunciation probabilities for more information. If you would like to use the version of this dictionary without probabilities, please see the [plain dictionary](https://raw.githubusercontent.com/MontrealCorpusTools/mfa-models/main/dictionary/english/mfa/English (India) MFA dictionary v3_1_0.dict).
Intended use#
This dictionary is intended for forced alignment of English transcripts.
This dictionary uses the MFA phone set for English, and was used in training the English MFA acoustic model. Pronunciations can be added on top of the dictionary, as long as no additional phones are introduced.
Performance Factors#
When trying to get better alignment accuracy, adding pronunciations is generally helpful, especially for different styles and dialects. The most impactful improvements will generally be seen when adding reduced variants that involve deleting segments/syllables common in spontaneous speech. Alignment must include all phones specified in the pronunciation of a word, and each phone has a minimum duration (by default 10ms). If a speaker pronounces a multisyllabic word with just a single syllable, it can be hard for MFA to fit all the segments in, so it will lead to alignment errors on adjacent words as well.
Ethical considerations#
Deploying any Speech-to-Text model into any production setting has ethical implications. You should consider these implications before use.
Demographic Bias#
You should assume every machine learning model has demographic bias unless proven otherwise. For pronunciation dictionaries, it is often the case that transcription accuracy and lexicon coverage for the prestige variety modeled in this dictionary compared to other variants. If you are using this dictionary in production, you should acknowledge this as a potential issue.
IPA Charts#
Consonants#
Obstruent symbols to the left of are unvoiced and those to the right are voiced.
Manner |
Labial |
Labiodental |
Dental |
Alveolar |
Alveopalatal |
Retroflex |
Palatal |
Velar |
Glottal |
|---|---|---|---|---|---|---|---|---|---|
Nasal |
Occurrences: 6,175 Examples: * simum: [s ɪ m ə m] * mater: [m eː ʈ ə ɾ] * cham: [k a m] * melon: [m ɛ l ə n] Occurrences: 1,241 Examples: * sami: [s ɑː mʲ i] * limit: [ʎ ɪ mʲ ɪ ʈ] * mixed: [mʲ ɪ k s] * mir: [mʲ ɪ ə] |
Occurrences: 3 Examples: |
Occurrences: 14,058 Examples: * don: [ɖ ɒ n] * tin: [ʈ ɪ n] * gwin: [ɟʷ ɪ n] * once: [ʋ ə n ʈ s] |
Occurrences: 2,150 Examples: * coney: [k ə ɲ i] * needs: [ɲ iː ɖ dʒ] * lenny: [l ɛ ɲ i] * niger: [ɲ iː ʒ ɛː ɾ] |
Occurrences: 2,325 Examples: * song: [s a ŋ] * franc: [f ɹ a ŋ k] * lanka: [l a ŋ k ə] * angus: [a ŋ ɡ ə s] |
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Stop |
Occurrences: 5,980 Examples: * prism: [p ɹ ɪ z ə m] * price: [p ɾ aj s] * paint: [p eː n] * piano: [p i ɑː n oː] Occurrences: 166 Examples: * guppy: [ɡ ə pʲ i] * puppy: [p ə pʲ i] * puget: [pʲ ʉː dʒ ɪ ʈ] * poppy: [p ɒ pʲ i] Occurrences: 2 Examples: Occurrences: 3,810 Examples: * rebel: [ɾ ɛ b ə l] * stabs: [s ʈ a b z] * baer: [b ɛː] * boil: [b ɔj l] Occurrences: 721 Examples: * baby: [b eː bʲ i] * began: [bʲ ɪ ɡ a n] * built: [bʲ ɪ l ʈ] * rugby: [ɾ ə ɟ bʲ i] |
Occurrences: 795 Examples: * thor: [t̪ ɒː] * thad: [t̪ a ɖ] * path: [p ɑː t̪] * fifth: [fʲ ɪ t̪] Occurrences: 291 Examples: * birth: [b ɜː d̪] * meath: [mʲ iː d̪] * this: [d̪ ɪ s] * with: [ʋ ɪ d̪] |
Occurrences: 11,037 Examples: * skirt: [s k ɜː ʈ] * trees: [ʈ ɾ iː z] * trial: [ʈ ɾ aj ə l] * turn: [ʈ ɜː n] Occurrences: 3,152 Examples: * cited: [s aj ʈʲ ɪ ɖ] * dante: [ɖ a n ʈʲ i] * utica: [j ʉː ʈʲ ɪ k ə] * empty: [ɛ m p ʈʲ i] Occurrences: 30 Examples: * twist: [ʈʷ ɪ s ʈ] * tweed: [ʈʷ iː ɖ] * twin: [ʈʷ ɪ n] * twig: [ʈʷ ɪ ɡ] Occurrences: 9,192 Examples: * lords: [l ɒː ɖ z] * woods: [ʋ ʊ ɖ z] * amid: [ə mʲ ɪ ɖ] * arid: [a ɾ ɪ ɖ] |
Occurrences: 2,045 Examples: * clad: [c ʎ a ɖ] * crate: [c ɹ eː ʈ] * creek: [c ɹ iː k] * cale: [c eː l] Occurrences: 119 Examples: * quick: [cʷ ɪ k] * query: [cʷ ɪ ɾ i] * quit: [cʷ ɪ ʈ] * quine: [cʷ ɪ n] Occurrences: 615 Examples: * igloo: [ɪ ɟ ʎ ʉː] * begin: [b ə ɟ ɪ n] * gig: [ɟ ɪ ɡ] * grate: [ɟ ɹ eː ʈ] Occurrences: 24 Examples: * guido: [ɟʷ iː ɖ oː] * gwen: [ɟʷ ɛ n] * gwin: [ɟʷ ɪ n] |
Occurrences: 7,875 Examples: * can: [k ə n] * punk: [p ə ŋ k] * cask: [k ɑː s k] * carlo: [k ɑː l oː] Occurrences: 176 Examples: * quiet: [kʷ aj ɪ ʈ] * quasi: [kʷ ɑ s i] * fuqua: [f ə kʷ ə] * quan: [kʷ ɒ n] Occurrences: 2,053 Examples: * gooch: [ɡ ʉː tʃ] * going: [ɡ oː ɪ ŋ] * whig: [ʋ ɪ ɡ] * galen: [ɡ eː l ə n] Occurrences: 19 Examples: * guo: [ɡʷ oː] * guang: [ɡʷ ɑː ŋ] * guam: [ɡʷ ɑː m] |
Occurrences: 2 Examples: * often: [ɒː f ʔ ə n] |
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Affricate |
Occurrences: 1,373 Examples: * cheat: [tʃ iː ʈ] * cha: [tʃ ɑː] * gulch: [ɡ ə l tʃ] * cham: [tʃ a m] Occurrences: 2,623 Examples: * hinge: [ç ɪ n dʒ] * image: [ɪ mʲ ɪ dʒ] * aged: [eː dʒ ɖ] * jaw: [dʒ ɒː] |
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Sibilant |
Occurrences: 12,917 Examples: * sand: [s a n] * place: [p l eː s] * plus: [p l ə s] * heist: [h aj s ʈ] Occurrences: 6,332 Examples: * rows: [ɾ oː z] * ism: [ɪ z ə m] * poles: [p oː l z] * aslan: [a z l ə n] |
Occurrences: 2,717 Examples: * shri: [ʃ ɹ iː] * ashby: [a ʃ bʲ i] * fish: [fʲ ɪ ʃ] * share: [ʃ ɛː] Occurrences: 174 Examples: * azure: [a ʒ ə] * hajj: [h ɑ ʒ] * asian: [eː ʒ ə n] * niger: [ɲ iː ʒ ɛː] |
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Fricative |
Occurrences: 2,768 Examples: * franc: [f ɹ a ŋ k] * fuzzy: [f ə z i] * chief: [tʃ iː f] * shaft: [ʃ ɑː f ʈ] Occurrences: 811 Examples: * fever: [fʲ iː ʋ ə] * finch: [fʲ ɪ n tʃ] * feud: [fʲ ʉː ɖ] * fiji: [fʲ iː dʒ iː] |
Occurrences: 323 Examples: * haig: [ç eː ɡ] * hail: [ç eː l] * hayes: [ç eː z] * hit: [ç ɪ ʈ] |
Occurrences: 1,327 Examples: * hurt: [h ɜː ʈ] * half: [h aː f] * hoped: [h oː p ʈ] * house: [h aw s] |
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Approximant |
Occurrences: 4 Examples: |
Occurrences: 4,455 Examples: * valor: [ʋ eː l ə] * grave: [ɟ ɹ eː ʋ] * wound: [ʋ aw n ɖ] * wars: [ʋ aː z] |
Occurrences: 9,256 Examples: * razed: [ɹ eː z ɖ] * riker: [ɹ aj k ə] * prix: [p ɹ iː] * kerry: [c ɛ ɹ i] |
Occurrences: 477 Examples: * utah: [j ʉː ʈ aː] * yeah: [j ɛː] * yahoo: [j ɑː h ʉː] |
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Tap |
Occurrences: 3,791 Examples: * cater: [c eː ʈ ə ɾ] * rib: [ɾ ɪ b] * grass: [ɡ ɾ ɑː s] * roads: [ɾ oː ɖ dʒ] |
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Lateral |
Occurrences: 8,531 Examples: * loose: [l ʉː s] * pilot: [p aj l ə ʈ] * slavs: [s l a ʋ z] * cello: [s ɛ l oː] |
Occurrences: 3,064 Examples: * liang: [ʎ i ɑː ŋ] * leroy: [ʎ iː ɹ ɔj] * liver: [ʎ ɪ ʋ ə ɾ] * belly: [b ɛ ʎ i] |
Vowels#
Vowel symbols to the left of are unrounded and those to the right are rounded.
Front |
Near-Front |
Central |
Near-Back |
Back |
|
|---|---|---|---|---|---|
Close |
Occurrences: 4,474 Examples: * dairy: [ɖ ɛː ɾ i] * percy: [p ɜː s i] * ready: [ɾ ɛ ɖ i] * paley: [p a ʎ i] Occurrences: 2,968 Examples: * these: [d̪ iː dʒ] * tree: [tʃ ɹ iː] * seal: [s iː l] * media: [mʲ iː ɖ ɪ ə] |
Occurrences: 285 Examples: * ruby: [ɾ ʉ bʲ i] * rome: [ɹ ʉ m] * dumas: [ɖ ʉ m ə z] * duet: [ɖ ʉ ɪ ʈ] Occurrences: 2,045 Examples: * tool: [ʈ ʉː l] * cuban: [c ʉː b ə n] * jesu: [dʒ iː z ʉː] * debut: [ɖ eː bʲ ʉː] |
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Occurrences: 17,531 Examples: * tying: [ʈ aj ɪ ŋ] * mixed: [mʲ ɪ k s ʈ] * intra: [ɪ n ʈ ɹ ə] * pinch: [p ɪ n tʃ] |
Occurrences: 1,045 Examples: * pull: [p ʊ l] * room: [ɹ ʊ m] * goal: [ɡ ɒ ʊ l] * goods: [ɡ ʊ ɖ z] |
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Close-Mid |
Occurrences: 0 Examples: Occurrences: 4,168 Examples: * place: [p l eː s] * elena: [ɛ l eː n ə] * veins: [ʋ eː n z] * lane: [l eː n] |
Occurrences: 0 Examples: Occurrences: 3,091 Examples: * sonia: [s oː ɲ i ə] * homes: [h oː m dʒ] * bozo: [b oː z oː] * prove: [p ɹ oː ʋ] |
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Occurrences: 24,031 Examples: * frege: [f ɹ ɛ ɡ ə] * giant: [dʒ aj ə n ʈ] * priam: [p ɹ aj ə m] * ebony: [ɛ b ə ɲ i] |
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Open-Mid |
Occurrences: 6,331 Examples: * adele: [ə ɖ ɛ l] * upset: [ə p s ɛ ʈ] * helen: [h ɛ l ə n] * edith: [ɛ ɖ ɪ t̪] Occurrences: 476 Examples: * flair: [f l ɛː] * bears: [b ɛː z] * fares: [f ɛː z] * wear: [ʋ ɛː] |
Occurrences: 49 Examples: * bury: [b ɜ ɹ i] * murr: [m ɜ] * herzl: [h ɜ ʈ s ə l] Occurrences: 1,233 Examples: * kern: [k ɜː n] * firth: [f ɜː t̪] * third: [t̪ ɜː ɖ] * burt: [b ɜː] |
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Open |
Occurrences: 5,574 Examples: * matic: [m a ʈʲ ɪ k] * nano: [n a n oː] * cabot: [k a b ə ʈ] * tasks: [ʈ a s k s] Occurrences: 562 Examples: * party: [p aː ʈʲ i] * wall: [ʋ aː l] * larva: [l aː ʋ ə] * sudan: [s ʉː ɖ aː n] |
Occurrences: 150 Examples: * han: [h ɑ n] * klan: [k l ɑ n] * vans: [ʋ ɑ n z] * not: [n ɑ] Occurrences: 1,988 Examples: * star: [s ʈ ɑː] * arc: [ɑː k] * arms: [ɑː m dʒ] * radha: [ɹ ɑː ɖ ə] Occurrences: 3,523 Examples: * drop: [ɖ ɾ ɒ p] * quan: [kʷ ɒ n] * blocs: [b l ɒ k s] * walsh: [ʋ ɒ l ʃ] Occurrences: 2,142 Examples: * hawks: [h ɒː k s] * jorge: [dʒ ɒː dʒ] * maud: [m ɒː ɖ] * orson: [ɒː s ə n] |
Diphthongs#
aj
aw
ɔj