What is IPL?
Iterative Pseudo-Labeling (IPL) is a semi-supervised algorithm used in speech recognition. The algorithm fine-tunes an existing model using both labeled and unlabeled data. IPL is known for efficiently performing multiple iterations of pseudo-labeling on unlabeled data as the acoustic model evolves.
How Does IPL Work?
IPL works by utilizing unlabeled data, which is not labeled with the correct transcriptions of speech, along with the labeled data, to fine-tune the existing model
Wav2vec-U is a new technique that helps computers to understand human speech better. Usually, machines need people to provide specific examples or recordings of human language for the computer to recognize and understand it - this is called labeled data. However, with wav2vec-U, the computer can analyze and learn from unlabeled language (speech that has not been pre-identified or categorized) without any human input.
How Does Wav2vec-U Work?
Wav2vec-U uses a process called self-supervised lea
XLSR: Multilingual Speech Recognition Model
Have you ever considered how speech recognition works for multiple languages? How do you train a model to understand various tongues?
The answer is XLSR - a multilingual speech recognition model built on wav2vec 2.0. The model is trained by solving a contrastive task over masked latent speech representations and jointly learns a quantization of the latents shared across languages. In simpler terms, XLSR is a speech recognition model that recognizes m