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update error calculator for rnnt

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This commit is contained in:
aky15 2023-04-26 10:34:48 +08:00
parent 490531ed51
commit bdb8a99da4
2 changed files with 11 additions and 5 deletions
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8
funasr/models/e2e_asr_transducer.py
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@ -386,7 +386,7 @@ class TransducerModel(AbsESPnetModel):
if not self.training and (self.report_cer or self.report_wer):
if self.error_calculator is None:
from espnet2.asr_transducer.error_calculator import ErrorCalculator
from funasr.modules.e2e_asr_common import ErrorCalculatorTransducer as ErrorCalculator
self.error_calculator = ErrorCalculator(
self.decoder,
@ -398,7 +398,7 @@ class TransducerModel(AbsESPnetModel):
report_wer=self.report_wer,
)
cer_transducer, wer_transducer = self.error_calculator(encoder_out, target)
cer_transducer, wer_transducer = self.error_calculator(encoder_out, target, t_len)
return loss_transducer, cer_transducer, wer_transducer
@ -889,6 +889,8 @@ class UnifiedTransducerModel(AbsESPnetModel):
if not self.training and (self.report_cer or self.report_wer):
if self.error_calculator is None:
from funasr.modules.e2e_asr_common import ErrorCalculatorTransducer as ErrorCalculator
self.error_calculator = ErrorCalculator(
self.decoder,
self.joint_network,
@ -899,7 +901,7 @@ class UnifiedTransducerModel(AbsESPnetModel):
report_wer=self.report_wer,
)
cer_transducer, wer_transducer = self.error_calculator(encoder_out, target)
cer_transducer, wer_transducer = self.error_calculator(encoder_out, target, t_len)
return loss_transducer, cer_transducer, wer_transducer
return loss_transducer, None, None

8
funasr/modules/e2e_asr_common.py
View File

@ -296,12 +296,13 @@ class ErrorCalculatorTransducer:
self.report_wer = report_wer
def __call__(
self, encoder_out: torch.Tensor, target: torch.Tensor
self, encoder_out: torch.Tensor, target: torch.Tensor, encoder_out_lens: torch.Tensor,
) -> Tuple[Optional[float], Optional[float]]:
"""Calculate sentence-level WER or/and CER score for Transducer model.
Args:
encoder_out: Encoder output sequences. (B, T, D_enc)
target: Target label ID sequences. (B, L)
encoder_out_lens: Encoder output sequences length. (B,)
Returns:
: Sentence-level CER score.
: Sentence-level WER score.
@ -312,7 +313,10 @@ class ErrorCalculatorTransducer:
encoder_out = encoder_out.to(next(self.decoder.parameters()).device)
batch_nbest = [self.beam_search(encoder_out[b]) for b in range(batchsize)]
batch_nbest = [
self.beam_search(encoder_out[b][: encoder_out_lens[b]])
for b in range(batchsize)
]
pred = [nbest_hyp[0].yseq[1:] for nbest_hyp in batch_nbest]
char_pred, char_target = self.convert_to_char(pred, target)