Skip to main content

Montreal Forced Aligner

Continuous Integration codecov Documentation Status Interrogate Status DOI

The Montreal Forced Aligner is a command line utility for performing forced alignment of speech datasets using Kaldi (http://kaldi-asr.org/).

Please see the documentation http://montreal-forced-aligner.readthedocs.io for installation and usage.

If you run into any issues, please check the mailing list for fixes/workarounds or to post a new issue.

Citation

MFA 3.0

For citing the latest version of MFA and its pretrained models, please use:

McAuliffe, Michael, Kaylynn Gunter, Michael Wagner, and Morgan Sonderegger (2026). Montreal Forced Aligner and the state of speech-to-text alignment in 2026. In Proceedings of Interspeech 2026.

@inproceedings{mcauliffe26_interspeech,
 author={McAuliffe, Michael and Gunter, Kaylynn and Wagner, Michael and Sonderegger, Morgan},
 title={{Montreal Forced Aligner and the state of speech-to-text alignment in 2026}},
 year=2026,
 booktitle={Proc. Interspeech 2026}
}

MFA 1.0

For citing the original software and models (upgrading to the MFA 3.X is recommended!), please use:

McAuliffe, Michael, Michaela Socolof, Sarah Mihuc, Michael Wagner, and Morgan Sonderegger (2017). Montreal Forced Aligner: trainable text-speech alignment using Kaldi. In Proceedings of Interspeech 2017.

@inproceedings{mcauliffe17_interspeech,
 author={McAuliffe, Michael and Socolof, Michaela and Mihuc, Sarah and Wagner, Michael and Sonderegger, Morgan},
 title={{Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi}},
 year=2017,
 booktitle={Proc. Interspeech 2017},
 pages={498--502},
 doi={10.21437/Interspeech.2017-1386}
}

Installation

You can install MFA either entirely through conda or a mix of conda for Kaldi and Pynini dependencies and Python packaging for MFA itself

Conda installation

MFA is hosted on conda-forge and can be installed via:

conda install -c conda-forge montreal-forced-aligner

in your environment of choice.

Source installation

If you'd like to install a local version of MFA or want to use the development set up, the easiest way is first create the dev environment from the yaml in the repo root directory:

conda env create -n mfa-dev -f environment.yml

Alternatively, the dependencies can be installed via:

conda install -c conda-forge python=3.11 kaldi librosa praatio tqdm requests colorama pyyaml pynini openfst baumwelch ngram

MFA can be installed in develop mode via:

pip install -e .[dev]

You should be able to see appropriate output from mfa version

Development

The test suite is run via tox -e py38-win or tox -e py38-unix depending on the OS, and the docs are generated via tox -e docs

Quick links

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

montreal_forced_aligner-3.4.2.tar.gz (27.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

montreal_forced_aligner-3.4.2-py3-none-any.whl (440.2 kB view details)

Uploaded Python 3

File details

Details for the file montreal_forced_aligner-3.4.2.tar.gz.

File metadata

  • Download URL: montreal_forced_aligner-3.4.2.tar.gz
  • Upload date:
  • Size: 27.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for montreal_forced_aligner-3.4.2.tar.gz
Algorithm Hash digest
SHA256 421f8cf3f619c9ec0f74ba695429cdf0112e055d82ca2d9f81c5771e6a8abf85
MD5 28ec97016979312ac945e1fd195e187a
BLAKE2b-256 58a44667bfb2aa52194774b724df4e9da3b0b1d0f6b8fccfdb5131fc229a3419

See more details on using hashes here.

File details

Details for the file montreal_forced_aligner-3.4.2-py3-none-any.whl.

File metadata

File hashes

Hashes for montreal_forced_aligner-3.4.2-py3-none-any.whl
Algorithm Hash digest
SHA256 7d61142a87acb404957da53694effa8ca27503c5b676c6d6b1696f7f44b3c0d6
MD5 9426f1735df141f2b4af09be27c91777
BLAKE2b-256 d42c509366391b2fec8225d1ef69005b1ef5052a8684085fe57563f230c1336b

See more details on using hashes here.

Release history Release notifications | RSS feed

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page