This model cannot provide accurate assessments of goodness of pronunciations or provide transcripts as it is trained to be accepting of variation in pronunciation to provide a reasonable alignment for Korean speech.

Bias, Risks, and Limitations

This model will perform best on the variety of speech that it was trained on. The speakers in the training data are all adult speakers, so child speech alignment may not be accurate.

Recommendations

When using this model on a variety that it was not trained on, better results can be attained by adapting the model to the data to be aligned first. See https://montreal-forced-aligner.readthedocs.io/en/latest/user_guide/workflows/adapt_acoustic_model.html and https://github.com/mmcauliffe/mfa-adaptation for example usage and scripts.

How to Get Started with the Model

Use the code below to get started with the model.

To get started, follow the instructions for installing MFA. To align files using this model, use the mfa align command.

Dictionary Details

Details for korean_mfa dictionary and G2P model

Source: wikipron
Orthography: Hangul
Phone set: MFA
Words: 79,188

Phones: 95
Graphemes: 2,250

IPA chart

Consonants

Manner	Labial	Alveolar	Retroflex	Palatal	Velar	Glottal
Nasal	m mː	n nː		ɲ	ŋ
Palatalized	mʲ mʲː
Stop	p b	t d		c ɟ	k ɡ
Tense	p͈	t͈ t͈ː		c͈	k͈ k͈ː
Aspirated	pʰ pʰː	tʰ tʰː		cʰ cʰː	kʰ kʰː
Unreleased	p̚	t̚			k̚
Labialized	pʷ bʷ	tʷ tʷː dʷ			kʷ kʷː ɡʷ
Palatalized	pʲ pʲː bʲ	tʲ dʲ
Affricate				tɕ tɕː dʑ
Tense				tɕ͈ tɕ͈ː
Aspirated				tɕʰ tɕʰː
Labialized				tɕʷ tɕʷː dʑʷ
Sibilant		s sː
Tense		s͈		ɕ͈
Aspirated		sʰ sʰː		ɕʰ
Labialized		sʷ
Fricative				ç ʝ		h ɦ
Labialized	ɸʷ
Approximant	w			j ɥ	ɰ
Tap		ɾ
Labialized		ɾʷ
Palatalized		ɾʲ
Lateral				ʎ ʎː
Lateral Tap			ɭ ɭː

Vowels

	Front	Central	Back
Close	i iː	ɨ ɨː	u uː

Close-Mid	e eː		o oː

Open-Mid	ɛ ɛː		ʌ ʌː
		ɐ
Open

Training Details

Training Data

Common Voice Korean

Source: https://voice.mozilla.org/en/datasets
License: CC-0
Dialects: N/A
Number of hours: 1.41
Number of utterances: 916
Number of speakers: 46
- Female speakers: 7
- Male speakers: 15
- Unknown speakers: 24

GlobalPhone Korean

Source: https://catalogue.elra.info/en-us/repository/browse/ELRA-S0200/
License: ELRA
Dialects: N/A
Number of hours: 20.88
Number of utterances: 8,007
Number of speakers: 99
- Female speakers: 50
- Male speakers: 49
- Unknown speakers: 0

Deeply Korean read speech corpus public sample

Source: https://www.openslr.org/97/
License: CC BY-NC-ND 4.0
Dialects: N/A
Number of hours: 2.93
Number of utterances: 1,697
Number of speakers: 2
- Female speakers: 2
- Male speakers: 0
- Unknown speakers: 0

ASR-KCSC A Korean Conversational Speech Corpus

Source: https://magichub.com/datasets/korean-conversational-speech-corpus/
License: CC BY-NC-ND 4.0
Dialects: N/A
Number of hours: 2.38
Number of utterances: 4,404
Number of speakers: 14
- Female speakers: 4
- Male speakers: 10
- Unknown speakers: 0

ASR-SKDuSC A Scripted Korean Daily-use Speech Corpus

Source: https://magichub.com/datasets/korean-scripted-speech-corpus-daily-use-sentence/
License: CC BY-NC-ND 4.0
Dialects: N/A
Number of hours: 3.90
Number of utterances: 5,240
Number of speakers: 10
- Female speakers: 5
- Male speakers: 5
- Unknown speakers: 0

Korean Single Speaker Speech Dataset

Source: https://www.kaggle.com/datasets/bryanpark/korean-single-speaker-speech-dataset
License: CC BY-NC-SA 4.0
Dialects: N/A
Number of hours: 12.86
Number of utterances: 12,854
Number of speakers: 40
- Female speakers: 1
- Male speakers: 0
- Unknown speakers: 0

Pansori TEDxKR

Source: http://www.openslr.org/58/
License: CC BY-NC-ND 4.0
Dialects: N/A
Number of hours: 2.69
Number of utterances: 2,989
Number of speakers: 41
- Female speakers: 9
- Male speakers: 32
- Unknown speakers: 0

Zeroth Korean

Source: https://openslr.org/40/
License: CC BY 4.0
Dialects: N/A
Number of hours: 52.87
Number of utterances: 22,720
Number of speakers: 115
- Female speakers: 70
- Male speakers: 45
- Unknown speakers: 0

Training Procedure

Preprocessing

Preprocessing include fixes and orthographic standardization to various corpora.

Training Hyperparameters

Training regime: Training configuration

Evaluation

Testing Data, Factors & Metrics

Testing Data

N/A

Factors

N/A

Metrics

N/A

Results

N/A

Summary

Technical Specifications

Model Architecture and Objective

HMM-GMM model

Software

This model was trained via the Montreal Forced Aligner.

Citation

BibTeX:

@techreport{mfa_korean_mfa_acoustic_2026,
	author={McAuliffe, Michael and Sonderegger, Morgan},
	title={Korean MFA acoustic model v3.3.0},
	address={\url{https://huggingface.co/MontrealCorpusTools/korean_mfa}},
	year={2026},
	month={Jun},
}

APA:

McAuliffe, M. & Sonderegger, M. (2026). Korean MFA acoustic model v3.3.0. Available at https://huggingface.co/MontrealCorpusTools/korean_mfa.

Contact

For questions and issues, please file an issue either for this model at https://huggingface.co/MontrealCorpusTools/korean_mfa/discussions or for larger MFA issues at https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/issues.