Spanish MFA dictionary v2.0.0#

  • Maintainer: Montreal Forced Aligner

  • Language: Spanish

  • Dialect: N/A

  • Phone set: MFA

  • Number of words: 86,746

  • Phones: a b c e f i j k l m n o p r s u w x ç ð ŋ ɟ ɟʝ ɡ ɣ ɲ ɾ ʃ ʎ ʝ β θ

  • License: CC BY 4.0

  • Compatible MFA version: v2.0.0

  • Citation:

@techreport{mfa_spanish_mfa_dictionary_2022,
	author={McAuliffe, Michael and Sonderegger, Morgan},
	title={Spanish MFA dictionary v2.0.0},
	address={\url{https://mfa-models.readthedocs.io/pronunciation dictionary/Spanish/Spanish MFA dictionary v2_0_0.html}},
	year={2022},
	month={Mar},
}
../../_images/full_logo_yellow.svg

Installation#

Install from the MFA command line:

mfa model download dictionary spanish_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.

Intended use#

This dictionary is intended for forced alignment of Spanish transcripts.

This dictionary uses the MFA phone set for Spanish, and was used in training the Spanish 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

Nasal

Occurrences:
24,314
Examples:
* monta:
[m o n a]
* gemma:
[ç e m a]
* moe:
[m o e]
* model:
[m o ð e l]
Occurrences:
43,181
Examples:
* green:
[ɡ ɾ e e n]
* hayan:
[a ʝ a n]
* hunda:
[u n a]
* bone:
[b o n e]
Occurrences:
2,589
Examples:
* tiña:
[ i ɲ a]
* cañar:
[k a ɲ a ɾ]
* niega:
[ɲ j e ɣ a]
* ñame:
[ɲ a m e]
Occurrences:
2,827
Examples:
* bingo:
[b i ŋ ɡ o]
* tenca:
[ e ŋ k a]
* ing:
[i ŋ]
* tengo:
[ e ŋ ɡ o]

Stop

Occurrences:
18,168
Examples:
* hype:
[ç i p e]
* sopa:
[s o p a]
* espín:
[e s p i n]
* apero:
[a p e ɾ o]
Occurrences:
7,643
Examples:
* bone:
[b o n e]
* bingo:
[b i ŋ ɡ o]
* vagón:
[b a ɣ o n]
* vivo:
[b i β o]
Occurrences:
39,054
Examples:
* atea:
[a e a]
* hotel:
[o e l]
* monta:
[m o n a]
* atril:
[a ɾ i l]
Occurrences:
11,351
Examples:
* hunda:
[u n a]
* wanda:
[w a n a]
* debió:
[ e β j o]
* dura:
[ u ɾ a]
Occurrences:
2,600
Examples:
* queso:
[c e s o]
* kebab:
[c e β a β]
* quede:
[c e ð e]
* kilos:
[c i l o s]
Occurrences:
213
Examples:
* guido:
[ɟ i ð o]
* guías:
[ɟ i a s]
* guisa:
[ɟ i s a]
* guía:
[ɟ i a]
Occurrences:
25,646
Examples:
* sox:
[s o k s]
* kvas:
[k β a s]
* loca:
[l o k a]
* rasca:
[r a s k a]
Occurrences:
2,710
Examples:
* green:
[ɡ ɾ e e n]
* bingo:
[b i ŋ ɡ o]
* golf:
[ɡ o l f]
* omc:
[o m ɡ]

Affricate

Occurrences:
2,769
Examples:
* chino:
[ i n o]
* achín:
[a i n]
* cloch:
[k l o ]
* chigi:
[ i ʝ i]
Occurrences:
570
Examples:
* yola:
[ɟʝ o l a]
* yagüe:
[ɟʝ a ɣ w e]
* yak:
[ɟʝ a k]
* jet:
[ɟʝ e ]

Sibilant

Occurrences:
64,275
Examples:
* ries:
[r j e s]
* hules:
[u l e s]
* césar:
[s e s a ɾ]
* sox:
[s o k s]
Occurrences:
360
Examples:
* shawn:
[ʃ a n]
* idish:
[i ð i ʃ]
* bajux:
[b a x u ʃ]
* shore:
[ʃ o ɾ e]

Fricative

Occurrences:
8,541
Examples:
* flojo:
[f l o x o]
* ferri:
[f e r i]
* golf:
[ɡ o l f]
* fort:
[f o r ]
Occurrences:
14,848
Examples:
* césar:
[θ e s a ɾ]
* cercó:
[θ e r k o]
* lucen:
[l u θ e n]
* ceará:
[θ e a ɾ a]
Occurrences:
34,784
Examples:
* ready:
[r e a ð i]
* oídio:
[o i ð j o]
* adiar:
[a ð j a ɾ]
* model:
[m o ð e l]
Occurrences:
3,413
Examples:
* gilí:
[ç i l i]
* hype:
[ç i p e]
* gemma:
[ç e m a]
* geo:
[ç e o]
Occurrences:
2,081
Examples:
* hayan:
[a ʝ a n]
* traia:
[ ɾ a ʝ a]
* buyei:
[b u ʝ e i]
* ayudó:
[a ʝ u ð o]

Approximant

Occurrences:
3,951
Examples:
* wayne:
[w a i n e]
* wanda:
[w a n a]
* wicca:
[w i k a]
* hawái:
[x a w a i]
Occurrences:
14,659
Examples:
* ries:
[r j e s]
* oídio:
[o i ð j o]
* adiar:
[a ð j a ɾ]
* debió:
[ e β j o]

Tap

Occurrences:
41,316
Examples:
* green:
[ɡ ɾ e e n]
* adiar:
[a ð j a ɾ]
* césar:
[s e s a ɾ]
* atril:
[a ɾ i l]

Trill

Occurrences:
19,390
Examples:
* ries:
[r j e s]
* ready:
[r e a ð i]
* arrow:
[a r o u]
* ferri:
[f e r i]

Lateral

Occurrences:
27,378
Examples:
* gilí:
[ç i l i]
* laho:
[l a o]
* hules:
[u l e s]
* yola:
[ɟʝ o l a]
Occurrences:
2,148
Examples:
* allah:
[a ʎ a]
* tallo:
[ a ʎ o]
* hello:
[e ʎ o]
* belle:
[b e ʎ e]

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:
53,822
Examples:
* gilí:
[ç i l i]
* ready:
[r e a ð i]
* oídio:
[o i ð j o]
* hype:
[ç i p e]
Occurrences:
17,452
Examples:
* hules:
[u l e s]
* hunda:
[u n a]
* arrow:
[a r o u]
* sutil:
[s u i l]

Close-Mid

Occurrences:
74,430
Examples:
* atea:
[a e a]
* ries:
[r j e s]
* green:
[ɡ ɾ e e n]
* ready:
[r e a ð i]
Occurrences:
73,294
Examples:
* oídio:
[o i ð j o]
* laho:
[l a o]
* bone:
[b o n e]
* bingo:
[b i ŋ ɡ o]

Open-Mid

Open

Occurrences:
123,922
Examples:
* atea:
[a e a]
* ready:
[r e a ð i]
* laho:
[l a o]
* hayan:
[a ʝ a n]