Alok Prasad

Thanks For Sharing!

> Ok finally got it to work here are the results: > > Raspberry Pi4 4GB > Model : L128_small_pretrain > **Fastspeech :** > MEL Calculation: > 2.8617560863494873 > >...

i would say..Read..learn..dig more..i am also not an ML Guy..:)

@LifaSun where you able to resolve this?

@tuanad121 , can you share your trained model of Tacotron2 for Lpcnet , ? Did you trained LPCNET also? Is there any difference in sysnthesis using test_lpcnet.py if we use...

@MlWoo i did some changes in fastspeech for integrating with lpcnet here are my changes 1.First prepossessed audio (ljspeech) and converted it to pcm(s16) ``` mkdir -p dataset/LJSpeech-1.1/pcms for i...

@MlWoo I did some inference time for Fastspeech its actually faster than Tacotron2 on CPU. eg. for 12 sec audio mel generation is taking about 1.2sec on Single Core CPU.

@MlWoo I have right now integrated fastspeech and squeewave https://github.com/alokprasad/fastspeech_squeezewave

@MlWoo i know you are not working on this , but just wanted too see if you faced any issue similar to below while integrating tacotron2 and lpcnet ``` ,...