Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Role in this project:
ML Engineer Contributions:2 reviews, 2 commits, 10 PRs in 1 day
Contributions summary:Andros contributed to the `facebookresearch/fairseq` repository by adding scripts for generating and evaluating embeddings and logits for a speech classification task. These scripts utilize the fairseq framework, specifically within the wav2vec and xlsr submodules, indicating work related to audio processing and machine learning model inference. Additionally, the user fixed an issue in the MMS ASR inference script by reordering the decoded output, indicating involvement in Automatic Speech Recognition (ASR) tasks. The user also created a Colab tutorial for MMS ASR inference.
aipythonsequence-to-sequencepytorchartificial-intelligence
Unified automatic quality assessment for speech, music, and sound.
Contributions:1 review, 7 PRs, 16 pushes in 5 months
speech