facebook/s2t-small-mustc-en-ro-st

Speech to Text Transformer (S2T) model trained for end-to-end Speech Translation (ST) It uses a convolutional downsampler to reduce the length of speech inputs by 3/4th before they are fed into the encoder . The model is trained with standard autoregressive cross-entropy loss and generates the transcripts autoregressively . This model can be used for English speech to Romanian text translation . It is trained on English-Romanian subset of MuST-C, a multilingual speech translation corpus whose size and quality facilitates the training of speech translation from English into several languages . To use this model, install the torchaudio package before running this,