diff --git a/modules/dvector.py b/modules/dvector.py
index 56260b5..9b4bfa9 100644
--- a/modules/dvector.py
+++ b/modules/dvector.py
@@ -1,6 +1,7 @@
 """Build a model for d-vector speaker embedding."""
 
 import abc
+import math
 from typing import List
 
 import torch
@@ -48,10 +49,18 @@ def embed_utterance(self, utterance: Tensor) -> Tensor:
         if utterance.ndim == 3:
             utterance = utterance.squeeze(0)
 
-        if utterance.size(1) <= self.seg_len:
+        if utterance.size(0) <= self.seg_len:
             embed = self.forward(utterance.unsqueeze(0)).squeeze(0)
         else:
-            segments = utterance.unfold(0, self.seg_len, self.seg_len // 2)
+            # Pad to multiple of hop length
+            hop_len = self.seg_len // 2
+            tgt_len = math.ceil(utterance.size(0) / hop_len) * hop_len
+            padded = torch.cat(
+                [utterance, torch.zeros(tgt_len - utterance.size(0), utterance.size(1))]
+            )
+
+            segments = padded.unfold(0, self.seg_len, self.seg_len // 2)
+            segments = segments.transpose(1, 2)  # (batch, seg_len, mel_dim)
             embeds = self.forward(segments)
             embed = embeds.mean(dim=0)
             embed = embed.div(embed.norm(p=2, dim=-1, keepdim=True))