Comments (2)
Hello @rlawoqls7
I am not sure if using the CTC loss on the decoder outputs could work well.
We previously used the CTC loss with the encoder, complementing the decoder's cross-entropy loss, as on this diagram. It was a different task though, lipreading.
To add the CTC loss, you could first project the encoder outputs to a dimension equal to the vocabulary size plus one, and call tf.nn.ctc_loss with the projected encoder outputs as your inputs. Additionally, you may have to convert the labels tensor from the current format (a sequence of integers) to the tf.SparseTensor representation.
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Please let us know in case you are still facing difficulties with the implementation.
Christian @saamc may be able to assist, as he has recently explored some ideas based on the CTC loss.
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