Deep neural networks for voice conversion (voice style transfer) in Tensorflow
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Hi, @Huishou TIMIT is a speech dataset aligned with its phonemes, the net1 is a speech recognizer trained with the speech and the phoenemes equivalent, then pass the recognized from net1 to net2, net2 is just synthetizing net1 prediction. That's why is important to use a dataset for net1 with lots of speakers to get a good prediction of what the speaker said. #92
Hi, @Huishou TIMIT is a speech dataset aligned with its phonemes, the net1 is a speech recognizer trained with the speech and the phoenemes equivalent, then pass the recognized from net1 to net2, net2 is just synthetizing net1 prediction. That's why is important to use a dataset for net1 with lots of speakers to get a good prediction of what the speaker said.
Hi, @Huishou TIMIT is a speech dataset aligned with its phonemes, the net1 is a speech recognizer trained with the speech and the phoenemes equivalent, then pass the recognized from net1 to net2, net2 is just synthetizing net1 prediction. That's why is important to use a dataset for net1 with lots of speakers to get a good prediction of what the speaker said.
Originally posted by @carlfm01 in https://github.com/andabi/deep-voice-conversion/issues/52#issuecomment-459856993