metadata

language:
  - ca
library_name: nemo
datasets:
  - mozilla-foundation/common_voice_11_0
thumbnail: null
tags:
  - automatic-speech-recognition
  - speech
  - audio
  - citrinet
  - pytorch
  - NeMo
  - hf-asr-leaderboard
license: cc-by-4.0
model-index:
  - name: stt-ca-citrinet-512
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Mozilla Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: ca
          split: test
          args:
            language: en
        metrics:
          - name: Test WER
            type: wer
            value: 6.684

Aina Project's Catalan text-to-speech model

Model description

This model was fine-tuned from a pre-trained Spanish stt-es-citrinet-512 model using the NeMo toolkit.

Intended uses and limitations

You can use this model for Automatic Speech Recognition (ASR) in catalan.

How to use

Usage

Requiered libraries:

pip install nemo_toolkit['all']

Clone the repository to download the model:

git clone https://huggingface.co/projecte-aina/stt-ca-citrinet-512

Given that NEMO_PATH is the path that points to the downloaded stt-ca-citrinet-512.nemo file, to do inference over a set of .wav files you should:

# Load the model
model = nemo_asr.models.EncDecCTCModel.restore_from(NEMO_PATH)

# Create a list pointing to the audio files
paths2audio_files = ["audio_1.wav", ..., "audio_n.wav"]

# Fix the batch size to whatever number suits your purpose
batch_size = 8

# Transcribe the audio files
transcriptions = model.transcribe(paths2audio_files=paths2audio_files,
                                 batch_size=batch_size)
# Visualize the transcriptions
print(transcriptions)

Additional information

Author

Text Mining Unit (TeMU) at the Barcelona Supercomputing Center ([email protected])

Contact information

For further information, send an email to [email protected]

Copyright

Licensing Information

Attribution 4.0 International (CC BY 4.0)

Funding

This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.

Disclaimer

Click to expand

The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.

When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of Artificial Intelligence.

In no event shall the owner and creator of the models (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.