athena.models.asr.av_mtl_seq2seq

a implementation of multi-task model with attention and ctc loss

Module Contents

Classes

AV_MtlTransformer

In speech recognition, adding CTC loss to Attention-based seq-to-seq model is known to

class athena.models.asr.av_mtl_seq2seq.AV_MtlTransformer(data_descriptions, config=None)

Bases: athena.models.base.BaseModel

In speech recognition, adding CTC loss to Attention-based seq-to-seq model is known to help convergence. It usually gives better results than using attention alone.

SUPPORTED_MODEL

default_config

call(samples, training=None)

call function in keras layers

get_loss(outputs, samples, training=None)

get loss used for training

compute_logit_length(input_length)

compute the logit length

reset_metrics()

reset the metrics

restore_from_pretrained_model(pretrained_model, model_type='')

A more general-purpose interface for pretrained model restoration :param pretrained_model: checkpoint path of mpc model :param model_type: the type of pretrained model to restore

decode(samples, hparams=None, lm_model=None)

Initialization of the model for decoding, decoder is called here to create predictions

Parameters

• samples – the data source to be decoded

• hparams – decoding configs are included here

• lm_model – lm model

Returns:

predictions: the corresponding decoding results