english_us_arpa

Model Card for english_us_arpa

<!-- Provide a quick summary of what the model is/does. -->

This MFA model is for aligning US English using the ARPAbet phone set.

• Model details
• Uses
• Performance Factors
• Dictionary Details
• Training Details
• Evaluation
• Contact

Model Details

Model Description

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• Developed by: Michael McAuliffe
• Funded by: N/A
• Model type: Montreal Forced Aligner model
• Language(s) (NLP): English
• License: cc-by-4.0

Uses

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Direct Use

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This model is intended to be used for forced alignment of US English. Other varieties of English (e.g. UK, Indian, Nigerian Englishes) may have inconsistent performance. Please see https://montreal-forced-aligner.readthedocs.io/en/latest/user_guide/troubleshooting.html for details on common fixes.

Out-of-Scope Use

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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 of US English.

Bias, Risks, and Limitations

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

Recommendations

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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 english_us_arpa dictionary and G2P model

• Source: wikipron
• Orthography: Latin
• Phone set: ARPA
• Words: 266,823

• Phones: 39
• Graphemes: 35

IPA chart

Consonants

Vowels

Diphthongs

• OY
• AY
• AW

Training Details

Training Data

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LibriSpeech English

• Source: https://openslr.org/12/
• License: CC BY 4.0
• Dialects: us
• Number of hours: 982.10
• Number of utterances: 292,367
• Number of speakers: 2,484
  • Female speakers: 1,283
  • Male speakers: 1,201
  • Unknown speakers: 0

Training Procedure

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Preprocessing

Preprocessing include fixes and orthographic standardization to various corpora.

Training Hyperparameters

• Training regime: Training configuration

Evaluation

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Testing Data, Factors & Metrics

Testing Data

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N/A

Factors

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N/A

Metrics

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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

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BibTeX:

@techreport{mfa_english_us_arpa_acoustic_2026,
	author={McAuliffe, Michael and Sonderegger, Morgan},
	title={English (US) ARPA acoustic model v3.3.0},
	address={\url{https://huggingface.co/MontrealCorpusTools/english_us_arpa}},
	year={2026},
	month={Jun},
}

APA:

McAuliffe, M. & Sonderegger, M. (2026). English (US) ARPA acoustic model v3.3.0. Available at https://huggingface.co/MontrealCorpusTools/english_us_arpa.

Contact

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