Open rohithkodali opened 5 years ago
Hi rohithkodali,
It's true, the test_sequence will need to be sliced to be compatible with UIS-RNN. I plan on revisiting the script in the near future.
FYI. I tried to split entire test set by exact 100 utterances.
test_sequences_2 = []
test_sequences_block = []
test_cluster_ids_2 = []
test_cluster_ids_block = []
count1 = 0
for test_sequence, test_cluster_id in zip(test_sequences, test_cluster_ids):
test_sequences_block.append(test_sequence)
test_cluster_ids_block.append(test_cluster_id)
count1 = count1 + 1
if count1 != 0 and count1 % 100 == 0:
test_sequences_2.append(test_sequences_block)
test_sequences_block = []
test_cluster_ids_2.append(test_cluster_ids_block)
test_cluster_ids_block = []
test_sequences = test_sequences_2
test_cluster_ids = test_cluster_ids_2
The accuracy was about 70%. Not that great. May be because of splitting methods...
Thanks for @kouohhashi. I insert the patch into demo.py
of uis-rnn but still getting ValueError: test_sequence must be 2-dim array.
I modified it as following and work!
test_seq_2 = []
test_id_2 = []
batch_seq = []
batch_id = []
count = 0
for test_sequence, test_cluster_id in zip(test_sequences, test_cluster_ids):
batch_seq.append(test_sequence)
batch_id.append(test_cluster_id)
count += 1
if count != 0 and count % 100 == 0:
test_seq_2.append(batch_seq)
batch_seq = []
test_id_2.append(batch_id)
batch_id = []
# (45,100,256) -> [array(100,256), array(100,256) .... ]
res = np.empty(len(test_seq_2), object)
res[:] = [np.array(a) for a in test_seq_2 ]
test_sequences = res
test_cluster_ids = test_id_2
HI HarryVolek,
I have created embeddings for Timit model and generated the d-vectors as you explained in README but when i try to test the features in USI_RNN it throw the following error
"ValueError: test_sequence must be 2-dim array." guess we need to reshape the test_sequence