Overview
The Wav2Vec2Phoneme model was proposed in Simple and Effective Zero-shot Cross-lingual Phoneme Recognition (Xu et al.,
2021 by Qiantong Xu, Alexei Baevski, Michael Auli.
The abstract from the paper is the following:
Recent progress in self-training, self-supervised pretraining and unsupervised learning enabled well performing speech
recognition systems without any labeled data. However, in many cases there is labeled data available for related
languages which is not utilized by these methods. This paper extends previous work on zero-shot cross-lingual transfer
learning by fine-tuning a multilingually pretrained wav2vec 2.0 model to transcribe unseen languages. This is done by
mapping phonemes of the training languages to the target language using articulatory features. Experiments show that
