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---
language:
- pt
pipeline_tag: other
library_name: montreal-forced-aligner
tags:
- montreal-forced-aligner
- forced-alignment
license: cc-by-4.0
---
# Model Card for portuguese_mfa
<!-- Provide a quick summary of what the model is/does. -->
This MFA model is for aligning Portuguese across Brazil and Portugal dialects.
- [Model details](#model-details)
- [Uses](#uses)
- [Performance Factors](#how-to-get-started-with-the-model)
- [Dictionary Details](#dictionary-details)
- [Training Details](#training-details)
- [Evaluation](#evaluation)
- [Contact](#contact)
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Michael McAuliffe
- **Funded by:** N/A
- **Model type:** Montreal Forced Aligner model
- **Language(s) (NLP):** Portuguese
- **License:** cc-by-4.0
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
This model is intended to be used for forced alignment of Portuguese varieties that it was trained on (Portugal and Brazil). Please see https://montreal-forced-aligner.readthedocs.io/en/latest/user_guide/troubleshooting.html for details on common fixes.
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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 Portuguese speech.
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
This model will perform best on the variety of speech that it was trained on, with a bias towards Brazilian Portuguese. The speakers in the training data are all adult speakers, so child speech alignment may not be accurate.
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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](https://montreal-forced-aligner.readthedocs.io/en/latest/getting_started.html). To align files using this model, use the [mfa align](https://montreal-forced-aligner.readthedocs.io/en/latest/user_guide/workflows/alignment.html) command.
## Dictionary Details
#### Details for portuguese_portugal_mfa dictionary and G2P model
- **Source:** wikipron
- **Orthography:** Latin
- **Phone set:** MFA
- **Words:** 117,496
* **Phones:** 42
* **Graphemes:** 82
##### IPA chart
###### Consonants
| Manner | Labial | Labiodental | Dental | Alveolar | Alveopalatal | Palatal | Velar | Uvular |
| :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: |
| **Nasal** | m | | | n | | ɲ | | |
| **Stop** | p b | | | t d | | | k ɡ | |
| Labialized | | | | | | | kʷ ɡʷ | |
| **Affricate** | | | | | tʃ dʒ | | | |
| **Sibilant** | | | | s z | ʃ ʒ | | | |
| **Fricative** | | f v | ð | | | | | ʁ|
| **Approximant** | w w̃ | | | | | j j̃ | | |
| **Tap** | | | | ɾ | | | | |
| **Lateral** | | | | ɫ | | ʎ | | |
###### Vowels
#### Oral vowels
| | Front | Near-Front | Central | Near-Back | Back |
| :----: | :----: | :----: | :----: | :----: | :----: |
| **Close** | i | | ɨ | | u|
| | | | | | |
| **Close-Mid** | e | | | | o|
| | | | | | |
| **Open-Mid** | ɛ | | | | ɔ|
| | | | ɐ | | |
| **Open** | | | a | | |
#### Nasal vowels
| | Front | Near-Front | Central | Near-Back | Back |
| :----: | :----: | :----: | :----: | :----: | :----: |
| **Close** | ĩ | | | | ũ|
| | | | | | |
| **Close-Mid** | ẽ | | | | õ|
| | | | | | |
| **Open-Mid** | | | | | |
| | | | ɐ̃ | | |
| **Open** | | | | | |
#### Details for portuguese_brazil_mfa dictionary and G2P model
- **Source:** wikipron
- **Orthography:** Latin
- **Phone set:** MFA
- **Words:** 213,148
* **Phones:** 40
* **Graphemes:** 85
##### IPA chart
###### Consonants
| Manner | Labial | Labiodental | Alveolar | Alveopalatal | Palatal | Velar | Uvular | Glottal |
| :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: |
| **Nasal** | m | | n | | | | | |
| **Stop** | p b | | t d | | | k ɡ | | |
| Labialized | | | | | | kʷ ɡʷ | | |
| **Affricate** | | | | tʃ dʒ | | | | |
| **Sibilant** | | | s z | ʃ ʒ | | | | |
| **Fricative** | | f v | | | | | ʁ | h|
| **Approximant** | w w̃ | | | | j j̃ | | | |
| **Tap** | | | ɾ | | | | | |
| **Lateral** | | | l | | ʎ | | | |
###### Vowels
#### Oral vowels
| | Front | Near-Front | Central | Near-Back | Back |
| :----: | :----: | :----: | :----: | :----: | :----: |
| **Close** | i | | | | u|
| | | | | | |
| **Close-Mid** | e | | | | o|
| | | | | | |
| **Open-Mid** | ɛ | | | | ɔ|
| | | | ɐ | | |
| **Open** | | | a | | |
#### Nasal vowels
| | Front | Near-Front | Central | Near-Back | Back |
| :----: | :----: | :----: | :----: | :----: | :----: |
| **Close** | ĩ | | | | ũ|
| | | | | | |
| **Close-Mid** | ẽ | | | | õ|
| | | | | | |
| **Open-Mid** | | | | | |
| | | | ɐ̃ | | |
| **Open** | | | | | |
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
#### Brazilian_Portuguese_Conversational_Speech_Corpus
- **Source:** [More Information Needed]
- **License:** [More Information Needed]
- **Dialects:** N/A
- **Number of hours:** 5.80
- **Number of utterances:** 7,293
- **Number of speakers:** 10
- **Female speakers:** 6
- **Male speakers:** 4
- **Unknown speakers:** 0
#### Common Voice Portuguese
- **Source:** https://voice.mozilla.org/en/datasets
- **License:** [CC-0](https://creativecommons.org/publicdomain/zero/1.0/)
- **Dialects:** brazil, portugal
- **Number of hours:** 111.25
- **Number of utterances:** 95,429
- **Number of speakers:** 2,002
- **Female speakers:** 58
- **Male speakers:** 500
- **Unknown speakers:** 1,444
#### CORAA
- **Source:** [More Information Needed]
- **License:** [More Information Needed]
- **Dialects:** N/A
- **Number of hours:** 289.76
- **Number of utterances:** 400,516
- **Number of speakers:** 77,825
- **Female speakers:** 0
- **Male speakers:** 0
- **Unknown speakers:** 0
#### GlobalPhone Portuguese (Brazilian)
- **Source:** https://catalogue.elra.info/en-us/repository/browse/ELRA-S0201/
- **License:** [ELRA](https://www.elra.info/en/services-around-lrs/distribution/licensing/)
- **Dialects:** brazil
- **Number of hours:** 26.26
- **Number of utterances:** 10,344
- **Number of speakers:** 102
- **Female speakers:** 48
- **Male speakers:** 53
- **Unknown speakers:** 1
#### Multilingual LibriSpeech Portuguese
- **Source:** https://openslr.org/94/
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Dialects:** portugal
- **Number of hours:** 168.45
- **Number of utterances:** 39,230
- **Number of speakers:** 62
- **Female speakers:** 26
- **Male speakers:** 36
- **Unknown speakers:** 0
#### Multilingual TEDx Portuguese
- **Source:** https://openslr.org/100/
- **License:** [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/)
- **Dialects:** portugal
- **Number of hours:** 181.68
- **Number of utterances:** 92,172
- **Number of speakers:** 834
- **Female speakers:** 0
- **Male speakers:** 0
- **Unknown speakers:** 834
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing
Preprocessing include fixes and orthographic standardization to various corpora.
#### Training Hyperparameters
- **Training regime:** [Training configuration](config.yaml)
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
N/A
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
N/A
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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](https://montreal-forced-aligner.readthedocs.io/).
## Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
```
@techreport{mfa_portuguese_mfa_acoustic_2026,
author={McAuliffe, Michael and Sonderegger, Morgan},
title={Portuguese MFA acoustic model v3.3.0},
address={\url{https://huggingface.co/MontrealCorpusTools/portuguese_mfa}},
year={2026},
month={Jun},
}
```
**APA:**
```
McAuliffe, M. & Sonderegger, M. (2026). Portuguese MFA acoustic model v3.3.0. Available at https://huggingface.co/MontrealCorpusTools/portuguese_mfa.
```
## Contact
For questions and issues, please file an issue either for this model at https://huggingface.co/MontrealCorpusTools/portuguese_mfa/discussions or for larger MFA issues at https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/issues.