i’m using
spectrogram = log(MelSpectrogram(n_mels=80, n_fft=1024, sample_rate=sr)(waveform)+ 1e-10).squeeze()
as input for the model.
the error occurs here when calling decoder.forward
decoder = RNNTBeamSearch(
model = model,
blank=10,
step_max_tokens=24,
)
with torch.no_grad():
all_transcriptions = []
all_targets = []
for i, batch in enumerate(test_dataloader):
inputs, targets, input_lengths, target_lengths = batch
transcriptions,transcriptions_lengths = model.transcribe(inputs,input_lengths)
print(transcriptions_lengths)
results = []
for i in range(0,len(transcriptions)):
result = decoder.forward(transcriptions,transcriptions_lengths,128)
results.append(result)
i also tried with conformer_rnnt_model and the only case where it works is when i set both input_dim=80 and
encoding_dim=80.
thanks in advance for any help.