torchaudio.prototype.pipelines

The pipelines subpackage contains APIs to models with pretrained weights and relevant utilities.

RNN-T Streaming/Non-Streaming ASR

EMFORMER_RNNT_BASE_MUSTC

torchaudio.prototype.pipelines.EMFORMER_RNNT_BASE_MUSTC

Pre-trained Emformer-RNNT-based ASR pipeline capable of performing both streaming and non-streaming inference. The underlying model is constructed by torchaudio.models.emformer_rnnt_base() and utilizes weights trained on MuST-C release v2.0 [Cattoni et al., 2021] dataset using training script train.py here with num_symbols=501. Please refer to torchaudio.pipelines.RNNTBundle for usage instructions.

EMFORMER_RNNT_BASE_TEDLIUM3

torchaudio.prototype.pipelines.EMFORMER_RNNT_BASE_TEDLIUM3

Pre-trained Emformer-RNNT-based ASR pipeline capable of performing both streaming and non-streaming inference.

The underlying model is constructed by torchaudio.models.emformer_rnnt_base() and utilizes weights trained on TED-LIUM Release 3 dataset using training script train.py here with num_symbols=501.

Please refer to torchaudio.pipelines.RNNTBundle for usage instructions.