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New initialization for embedding layer and use phonemes count instead of symbols for embedding layer init

This commit is contained in:
Eren Golge 2019-01-09 16:00:57 +01:00
parent 916f5df5f9
commit c2637f114e
1 changed files with 7 additions and 4 deletions
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11
models/tacotron.py
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@ -1,7 +1,8 @@
# coding: utf-8
import torch
from torch import nn
from utils.text.symbols import symbols
from math import sqrt
from utils.text.symbols import symbols, phonemes
from layers.tacotron import Prenet, Encoder, Decoder, PostCBHG
@ -17,9 +18,11 @@ class Tacotron(nn.Module):
self.mel_dim = mel_dim
self.linear_dim = linear_dim
self.embedding = nn.Embedding(
len(symbols), embedding_dim, padding_idx=padding_idx)
print(" | > Number of characters : {}".format(len(symbols)))
self.embedding.weight.data.normal_(0, 0.3)
len(phonemes), embedding_dim, padding_idx=padding_idx)
print(" | > Number of characters : {}".format(len(phonemes)))
std = sqrt(2.0 / (len(phonemes) + embedding_dim))
val = sqrt(3.0) * std # uniform bounds for std
self.embedding.weight.data.uniform_(-val, val)
self.encoder = Encoder(embedding_dim)
self.decoder = Decoder(256, mel_dim, r)
self.postnet = PostCBHG(mel_dim)