def validation(args, model, device, val_loader, val_scp, val_utt2label):
logger.info("Starting Validation")
val_loss, val_scores = compute_loss(model, device, val_loader)
val_preds, val_labels = utt_scores(val_scores, val_scp, val_utt2label)
val_eer = compute_eer(val_labels, val_preds)
logger.info('===> Validation set: Average loss: {:.4f}\tEER: {:.4f}\n'.format(
val_loss, val_eer))
return val_loss, val_eer
def prediction(args, model, device, eval_loader, eval_scp, eval_utt2label):
logger.info("Starting evaluation")
eval_loss, eval_scores = compute_loss(model, device, eval_loader)
eval_preds, eval_labels = utt_scores(eval_scores, eval_scp, eval_utt2label)
eval_eer = compute_eer(eval_labels, eval_preds)
logger.info("===> Final predictions done. Here is a snippet")
logger.info('===> evalidation set: Average loss: {:.4f}\tEER: {:.4f}\n'.format(
eval_loss, eval_eer))
return eval_loss, eval_eer
def utt_eer(scores, utt2len, utt2label, key_list, threshold):
"""return eer using majority vote
"""
preds, labels = [], []
idx = 0
for key in key_list:
frames_per_utt = utt2len[key]
# majority vote
num_total = frames_per_utt
num_genuine = np.sum(scores[idx:idx + frames_per_utt] >= threshold)
num_spoof = num_total - num_genuine
idx = idx + frames_per_utt
if num_genuine > num_spoof:
preds.append(1)
else:
preds.append(0)
labels.append(utt2label[key])
return compute_eer(labels, preds)
def compute_utt_eer(scores, scp, utt2label, threshold):
"""utterance-based eer
"""
utt2len = ako.read_key_len(scp)
utt2label = ako.read_key_label(utt2label)
key_list = ako.read_all_key(scp)
preds, labels = [], []
idx = 0
for key in key_list:
frames_per_utt = utt2len[key]
avg_scores = np.average(scores[idx:idx + frames_per_utt])
idx = idx + frames_per_utt
if avg_scores < threshold:
preds.append(0)
else:
preds.append(1)
labels.append(utt2label[key])
eer = compute_eer(labels, preds)
confuse_mat = compute_confuse(labels, preds)
return eer, confuse_mat
def f_neg(threshold):
## Scipy tries to minimize the function
return compute_eer(true_labels, predictions >= threshold)