# sentence vector to sentence

I have implemented an auto-encoder that takes sentence vectors as input and at decoder the last layer outputs sentence vectors. I would like to convert sentence vectors to sentences. Is there any way to convert sentence vectors to sentences?

class AutoEncoder(nn.Module):

def __init__(self, embedding_dim, hidden_dim):

#Constructor
super().__init__()

self.fc=nn.Linear(embedding_dim,hidden_dim)
self.act1=nn.ReLU(0.2)
self.fc1=nn.Linear(hidden_dim,hidden_dim)
self.act2=nn.ReLU(0.2)
self.fc2=nn.Linear(hidden_dim,hidden_dim)
self.act3=nn.ReLU(0.2)
self.fc3=nn.Linear(hidden_dim,hidden_dim)
self.act4=nn.ReLU(0.2)
self.fc4=nn.Linear(hidden_dim,hidden_dim)
self.act5=nn.ReLU(0.2)
self.fc5=nn.Linear(hidden_dim,embedding_dim)
def forward(self, X):
l1=self.fc(X)
a1=self.act1(l1)
l2=self.fc1(a1)
a2=self.act2(l2)
l3=self.fc2(a2)
a3=self.act3(l3)
l4=self.fc3(a3)
a4=self.act4(l4)
l5=self.fc4(a4)
a5=self.act5(l5)
l6=self.fc5(a5)
return l6


Here I have considered word embeddings initially and converted them to sentence vectors by averaging. These vectors are given for auto encoder model.

Let me know whether we have any other approach where we can generate a sentence.

Any kind of reference is helpful.

• You could do it with an LSTM or any other recurrent network. However, averaging the vectors means that you are losing the original ordering of words, so you may consider obtaining the sentence vector in a different way. – noe Jan 11 at 17:55
• Do we have any approach to convert sentence vectors back to sentence – SS Varshini Jan 12 at 3:45