Comments (5)
Dear Hudson,
Sorry for the delay in my response, I have been busy working on the seq2seq model.
Regarding the Zaska and dtw scripts, they belong to the Signal Theory and Communications department at the UPC university in Catalonia (this project is being developed for my bachelor thesis).
I have contacted the people at the department to ask them if I can distribute these scripts. I'll get back to you as soon as I have a response
Regarding the resulting sound of the system, I am aware that it does not give very accurate results. You see, the scripts you write about belong to the 'baseline' of the system. This version was developed only to have a reference level of results quality, as we have been focusing our efforts (and still are) on the sequence-to-sequence model.
If you find a way to improve this baseline, that is great news, but we are not going to work on it anymore
As always, thank you for your interest in this project
Cheers!
from tfg-voice-conversion.
Dear Albert,
Thank you so much for your response. The seq2seq model is definitely a good idea.
And as a reference, you can also check up this company:https://lyrebird.ai/. They are trying to give out an API-level Voice Conversion Solution, for commercial purposes. And it seems they have a good team including Yoshua Bengio.
But as you can see, they still didn't reach a much higher quality as the Mixture Neural Network solution in your project, I mean, maybe they have set a peak level for the Voice Conversion Systems, which is still not very natural, so don't be discouraged if the seq2seq solution doesn't work much better than the Mixture Neural Network solution.
Best regards!
from tfg-voice-conversion.
@MissPassenger
I found that the ZASKA is an DTW toolkit developed by the UPC and,the dtw is a DTW tool inside of it.
so, I am trying to instead it with mfcc and dtw code in SPTK。
like this:
`
b=2
sox mfcc/${DIR_REF}/${FILENAME}_sil.wav mfcc/${DIR_REF}/${FILENAME}_sil.raw
sox mfcc/${DIR_TST}/${FILENAME}_sil.wav mfcc/${DIR_TST}/${FILENAME}_sil.raw
x2x +sf < mfcc/${DIR_REF}/${FILENAME}_sil.raw | frame -l 480 -p 80 | \
mfcc -l 480 -m 20 -s 16 > mfcc/${DIR_REF}/${FILENAME}.mfcc
x2x +sf < mfcc/${DIR_TST}/${FILENAME}_sil.raw | frame -l 480 -p 80 | \
mfcc -l 480 -m 20 -s 16 > mfcc/${DIR_TST}/${FILENAME}.mfcc
dtw -l 480 mfcc/${DIR_REF}/${FILENAME}.mfcc < mfcc/${DIR_TST}/${FILENAME}.mfcc >> ${DIR_DTW}/${FILENAME}_ascii.dtw
x2x +af ${DIR_DTW}/${FILENAME}_ascii.dtw ${DIR_DTW}/beam${b}/${FILENAME}.dtw
`
but the dtw command output a unreadable format for x2x command and build_datatable
ansd which seem to be ASCII
I use x2x +af to convert it but it fails.
Any idea?
Thanks.
from tfg-voice-conversion.
from tfg-voice-conversion.
That helps a lot~ many thanks.
from tfg-voice-conversion.
Related Issues (10)
- Does this work with fixed target speaker without parallel data? HOT 1
- What is or where is ”interpolate.py“? HOT 2
- May I pull an user guide to this repo? HOT 5
- Missing interpolate.py HOT 4
- The configuration of the mcep-gmm model HOT 2
- x2x error on decodew_aho.sh
- Cat't download successfully HOT 3
- about prepare data for mcp_gru.py
- I want to which function is for the MCEPs
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