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English (Nigeria) MFA dictionary v3.0.0#

  • Maintainer: Montreal Forced Aligner

  • Language: English

  • Dialect: Nigerian English

  • Phone set: MFA

  • Number of words: 56,338

  • Phones: a aj aw aː b bʲ c cʰ cʷ d dʒ dʲ d̪ e f fʲ h i iː j k kp kʰ kʷ l m mʲ n o p pʰ pʲ pʷ s t tʃ tʰ tʲ tʷ t̪ u uː v vʲ w z ç ð ŋ ɔ ɔj ɛ ɛː ɜ ɜː ɟ ɟʷ ɡ ɡb ɡʷ ɫ ɱ ɲ ɹ ʃ ʊ ʎ ʔ θ

  • License: CC BY 4.0

  • Compatible MFA version: v3.0.0

  • Citation:

@techreport{mfa_english_nigeria_mfa_dictionary_2024,
	author={McAuliffe, Michael and Sonderegger, Morgan},
	title={English (Nigeria) MFA dictionary v3.0.0},
	address={\url{https://mfa-models.readthedocs.io/pronunciation dictionary/English/English (Nigeria) MFA dictionary v3_0_0.html}},
	year={2024},
	month={Feb},
}

G2P models
../../_images/full_logo_yellow.svg

Installation#

Install from the MFA command line:

mfa model download dictionary english_nigeria_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 (Nigeria) MFA dictionary v3_0_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

Palatal

Velar

Glottal

Nasal
Occurrences:
11,447
Examples:
* maid:
[m e d]
* mario:
[m a ɹ i o]
* maps:
[m a p s]
* email:
[ɛ m e ɫ]
Occurrences:
2,723
Examples:
* mist:
[mʲ i s t]
* admit:
[a d mʲ i t]
* gimme:
[ɟ i mʲ iː]
* myth:
[mʲ i θ]
Occurrences:
11
Examples:
Occurrences:
23,049
Examples:
* agent:
[e dʒ ɛ n t]
* noise:
[n ɔj z]
* wound:
[w uː n d]
* down:
[d aw n]
Occurrences:
4,919
Examples:
* until:
[ɔ ɲ tʲ i ɫ]
* danny:
[d a ɲ i]
* minim:
[mʲ i ɲ i m]
* any:
[ɛ ɲ i]
Occurrences:
4,926
Examples:
* lying:
[l aj i ŋ]
* hang:
[h a ŋ]
* bling:
[b ʎ i ŋ ɡ]
* mango:
[m a ŋ ɡ o]

Stop Plain
Occurrences:
6,277
Examples:
* april:
[e p ɹ i ɫ]
* plato:
[p l e tʰ o]
* prove:
[p ɹ o v]
* spite:
[s p aj]
Occurrences:
1,118
Examples:
* pure:
[pʲ ɔ]
* lapis:
[l a pʲ i s]
* april:
[e pʲ i ɫ]
* puree:
[pʲ ʊ ɹ iː]
Occurrences:
9
Examples:
Occurrences:
7,632
Examples:
* rib:
[ɹ i b]
* bow:
[b o]
* biro:
[b aj ɹ o]
* beige:
[b e ʃ]
Occurrences:
1,475
Examples:
* bids:
[bʲ i d z]
* obeah:
[o bʲ i a]
* abc:
[e bʲ iː s iː]
* bida:
[bʲ i d a]
Occurrences:
93
Examples:
* thou:
[t̪ aw]
* death:
[d ɛ t̪]
* thing:
[t̪ i ŋ]
* third:
[t̪ aː d]
Occurrences:
70
Examples:
* these:
[d̪ iː s]
* other:
[ɔ d̪ a]
* their:
[d̪ ɛː]
* mouth:
[m aw d̪]
Occurrences:
16,736
Examples:
* stain:
[s t e n]
* treat:
[t ɹ iː t]
* split:
[s p ʎ i t]
* least:
[ʎ iː s t]
Occurrences:
4,694
Examples:
* unity:
[j uː ɲ i tʲ i]
* pity:
[pʰ i tʲ i]
* tune:
[tʲ uː n]
* multi:
[m ɔ ɫ tʲ i]
Occurrences:
95
Examples:
* twin:
[tʷ i n]
* twill:
[tʷ i ɫ]
* twist:
[tʷ i s t]
* twins:
[tʷ i n z]
Occurrences:
12,967
Examples:
* dance:
[d a n s]
* card:
[kʰ a d]
* you'd:
[j uː d]
* okada:
[o kʰ a d a]
Occurrences:
3,352
Examples:
* india:
[i ɲ dʲ i a]
* diya:
[dʲ iː a]
* dues:
[dʲ uː z]
* deans:
[dʲ iː n z]
Occurrences:
2,528
Examples:
* naked:
[n e c i d]
* clips:
[c ʎ i p s]
* skies:
[s c aj z]
* scars:
[s c aː z]
Occurrences:
304
Examples:
* queen:
[cʷ iː n]
* quill:
[cʷ i ɫ]
* query:
[cʷ i ɹ i]
* quit:
[cʷ i t]
Occurrences:
1,047
Examples:
* giver:
[ɟ i v a]
* green:
[ɟ ɹ iː n]
* gives:
[ɟ i v s]
* agree:
[a ɟ ɹ iː]
Occurrences:
64
Examples:
Occurrences:
10,174
Examples:
* think:
[θ i ŋ k]
* clef:
[k l ɛ f]
* score:
[s k ɔ]
* dock:
[d ɔ k]
Occurrences:
473
Examples:
* choir:
[kʷ aj a]
* akwa:
[a kʷ a]
* quake:
[kʷ e k]
* squad:
[s kʷ ɔ d]
Occurrences:
7,731
Examples:
* gad:
[ɡ a d]
* egos:
[ɛ ɡ o z]
* leg:
[l ɛ ɡ]
* rogue:
[ɹ o ɡ]
Occurrences:
45
Examples:
* gweje:
[ɡʷ ɛ dʒ e]
Occurrences:
13
Examples:
* that:
[d̪ a ʔ]
* put:
[pʰ ʊ ʔ]
* jet:
[dʒ ɛ ʔ]
* seat:
[s iː ʔ]

Aspirated
Occurrences:
4,634
Examples:
* pence:
[pʰ ɛ n s]
* paves:
[pʰ e v z]
* pens:
[pʰ ɛ n z]
* polka:
[pʰ ɔ ɫ k a]
Occurrences:
4,860
Examples:
* tare:
[tʰ ɛː]
* two:
[tʰ uː]
* team:
[tʰ iː m]
* too:
[tʰ uː]
Occurrences:
1,654
Examples:
* kills:
[cʰ i ɫ z]
* nyaki:
[ɲ a cʰ i]
* kebbi:
[cʰ ɛ bʲ i]
* kemi:
[cʰ ɛ mʲ i]
Occurrences:
5,045
Examples:
* cause:
[kʰ ɔ s]
* cola:
[kʰ o l a]
* kandy:
[kʰ a ɲ dʲ i]
* calf:
[kʰ a f]

Affricate
Occurrences:
2,424
Examples:
* fetch:
[f ɛ tʃ]
* rich:
[ɹ i tʃ]
* truth:
[tʃ uː t̪]
* touch:
[tʰ ɔ tʃ]
Occurrences:
3,814
Examples:
* badge:
[b a dʒ]
* jobs:
[dʒ ɔ p s]
* john:
[dʒ ɔ n]
* jar:
[dʒ a]

Sibilant
Occurrences:
25,322
Examples:
* slip:
[s ʎ i p]
* scoop:
[s k uː p]
* serum:
[s iː u m]
* asita:
[a s i t a]
Occurrences:
9,061
Examples:
* polls:
[pʰ o ɫ z]
* pens:
[pʰ ɛ n z]
* kinds:
[kʰ aj n z]
* zeal:
[z iː ɫ]
Occurrences:
5,476
Examples:
* shey:
[ʃ e]
* shove:
[ʃ ɔ v]
* clash:
[k l a ʃ]
* wash:
[w ɔ ʃ]

Fricative
Occurrences:
5,765
Examples:
* fault:
[f ɔ ɫ t]
* fight:
[f aj t]
* firs:
[f aː s]
* fold:
[f o ɫ d]
Occurrences:
1,608
Examples:
* fuel:
[fʲ ʊ ɛ ɫ]
* fifty:
[fʲ i f tʰ i]
* fear:
[fʲ i a]
* few:
[fʲ uː]
Occurrences:
3,935
Examples:
* move:
[m uː v]
* via:
[v aj a]
* river:
[ɹ aj v a]
* delve:
[d ɛ ɫ v]
Occurrences:
1,126
Examples:
* davis:
[d e vʲ i s]
* vicky:
[vʲ i cʰ i]
* views:
[vʲ uː s]
* vera:
[vʲ i ɹ a]
Occurrences:
1,798
Examples:
* worth:
[w ɔ θ]
* sith:
[s iː θ]
* maths:
[m a θ s]
* theft:
[θ ɛ f t]
Occurrences:
441
Examples:
* oaths:
[o ð z]
* dey:
[ð e]
* other:
[ɔ ð a]
* these:
[ð iː z]
Occurrences:
694
Examples:
* heath:
[ç iː θ]
* heavy:
[ç iː vʲ i]
* huge:
[ç uː dʒ]
* haze:
[ç e z]
Occurrences:
2,422
Examples:
* hand:
[h a n d]
* hole:
[h o ɫ]
* hire:
[h aj a]
* hans:
[h a n s]

Approximant
Occurrences:
2,589
Examples:
* white:
[w aj]
* wider:
[w aj d a]
* wild:
[w aj ɫ d]
* ewedu:
[ɛ w ɛ d uː]
Occurrences:
19,115
Examples:
* trim:
[tʃ ɹ i m]
* risk:
[ɹ i s k]
* guru:
[ɡ uː ɹ uː]
* react:
[ɹ iː a t]
Occurrences:
1,209
Examples:
* yaba:
[j a b a]
* yale:
[j e ɫ]
* azure:
[a z j ʊ a]
* ijaye:
[iː dʒ a j e]

Lateral
Occurrences:
9,196
Examples:
* flame:
[f l e m]
* late:
[l e t]
* clerk:
[k l a k]
* los:
[l ɔ s]
Occurrences:
7,411
Examples:
* hull:
[h ɔ ɫ]
* cells:
[s ɛ ɫ s]
* meals:
[mʲ iː ɫ z]
* fails:
[f e ɫ z]
Occurrences:
5,843
Examples:
* badly:
[b a d ʎ i]
* folic:
[f o ʎ i k]
* early:
[aː ʎ i]
* sleep:
[s ʎ iː p]

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:
40,457
Examples:
* mints:
[mʲ i n t s]
* being:
[bʲ iː i ŋ]
* tenth:
[tʰ i n θ]
* bobby:
[b ɔ bʲ i]
Occurrences:
6,260
Examples:
* meets:
[mʲ iː t s]
* deity:
[dʲ iː i tʲ i]
* read:
[ɹ iː d]
* leans:
[ʎ iː n z]
Occurrences:
4,063
Examples:
* rome:
[ɹ u m]
* torus:
[tʰ ɔ ɹ u s]
* yusuf:
[j u s ʊ f]
* mosun:
[m ʊ s u n]
Occurrences:
4,739
Examples:
* fruit:
[f ɹ uː t]
* who's:
[h uː z]
* tool:
[tʃ uː ɫ]
* umar:
[uː m a ɹ]
Occurrences:
3,803
Examples:
* puts:
[pʰ ʊ t s]
* pulls:
[pʰ ʊ ɫ z]
* moot:
[m ʊ t]
* old:
[ɔ ʊ ɫ d]

Close-Mid
Occurrences:
7,803
Examples:
* flame:
[f l e m]
* aim:
[e m]
* saint:
[s e n t]
* wade:
[w e d]
Occurrences:
7,104
Examples:
* don't:
[d o n]
* robe:
[ɹ o b]
* oyo:
[ɔj o]
* nodes:
[n o t s]

Open-Mid
Occurrences:
21,132
Examples:
* pedal:
[pʰ ɛ d a ɫ]
* tense:
[tʰ ɛ n s]
* jetty:
[dʒ ɛ tʰ i]
* trend:
[tʃ ɹ ɛ n]
Occurrences:
769
Examples:
* girl:
[ɡ ɛː ɫ]
* chair:
[tʃ ɛː]
* are:
[ɛː]
* bear:
[b ɛː]
Occurrences:
136
Examples:
* bury:
[b ɜ ɹ i]
Occurrences:
3
Examples:
Occurrences:
24,024
Examples:
* honey:
[h ɔ ɲ i]
* lung:
[l ɔ ŋ ɡ]
* more:
[m ɔ]
* false:
[f ɔ ɫ s]

Open
Occurrences:
35,564
Examples:
* basal:
[b a s a ɫ]
* blast:
[b l a s t]
* tower:
[tʰ aw a]
* buyer:
[b aj a]
Occurrences:
2,169
Examples:
* versa:
[v aː s a]
* turn:
[tʰ aː n]
* birth:
[b aː s]
* nerve:
[n aː v]

Diphthongs#

  • aj

  • aw

  • ɔj

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