espnet3.systems.esp2_asr.system.ASRSystem

source

class espnet3.systems.esp2_asr.system.ASRSystem(training_config: DictConfig | None = None, inference_config: DictConfig | None = None, metrics_config: DictConfig | None = None, publication_config: DictConfig | None = None, demo_config: DictConfig | None = None)

Bases: BaseSystem

ASR-specific system.

This system adds train_tokenizer (its log goes under training_config.tokenizer.save_path), run before train trains the tokenizer if it is not already cached.

Examples

>>> [s.name for s in ASRSystem.stages[:2]]
['create_dataset', 'train_tokenizer']

Initialize the system with optional stage configs.

• Parameters:
  • training_config – Training configuration for data preparation, statistics collection, and model training.
  • inference_config – Inference configuration used by the infer stage.
  • metrics_config – Measurement configuration used by the measure stage.
  • publication_config – Publication configuration for pack_model and upload_model stages.
  • demo_config – Demo configuration for the demo stage.

stages : ClassVar[tuple[StageSpec, ...]] = (StageSpec(name='create_dataset', config='training', log_dir='data_dir'), StageSpec(name='train_tokenizer', config='training', log_dir='tokenizer.save_path'), StageSpec(name='collect_stats', config='training', log_dir='stats_dir'), StageSpec(name='train', config='training', log_dir='exp_dir'), StageSpec(name='infer', config='inference', log_dir='inference_dir'), StageSpec(name='measure', config='metrics', log_dir='inference_dir'), StageSpec(name='pack_model', config=('training', 'publication'), log_dir=None), StageSpec(name='upload_model', config='publication', log_dir=None), StageSpec(name='pack_demo', config='demo', log_dir='pack.out_dir'), StageSpec(name='upload_demo', config='demo', log_dir='pack.out_dir'))

train(*args, **kwargs)

Train the model, training the tokenizer first if needed.

This stage checks for a cached tokenizer model and runs tokenizer training before delegating to the base training routine.

• Raises:RuntimeError – If neither dataset references nor dataset_dir exist.

train_tokenizer(*args, **kwargs)

Train a SentencePiece tokenizer based on configured text.

The text builder configured in training_config.tokenizer.text_builder is used to generate training text, which is then saved and consumed by the SentencePiece trainer.

• Raises:RuntimeError – If required tokenizer config is missing or invalid.