diff --git a/kokoro/pipeline.py b/kokoro/pipeline.py
index ad5f2a3..1737104 100644
--- a/kokoro/pipeline.py
+++ b/kokoro/pipeline.py
@@ -83,7 +83,7 @@ class KPipeline:
             print(f"⚠️ WARNING: Using EspeakG2P(language='{language}'). Chunking logic not yet implemented, so long texts may be truncated unless you split them with '\\n'.")
             self.g2p = espeak.EspeakG2P(language=language)
 
-    def load_voice(self, voice: str) -> torch.FloatTensor:
+    def load_single_voice(self, voice: str):
         if voice in self.voices:
             return self.voices[voice]
         if voice.endswith('.pt'):
@@ -98,6 +98,21 @@ class KPipeline:
         self.voices[voice] = pack
         return pack
 
+    """
+    load_voice is a helper function that lazily downloads and loads a voice:
+    Single voice can be requested (e.g. 'af_bella') or multiple voices (e.g. 'af_bella,af_jessica').
+    If multiple voices are requested, they are averaged.
+    Delimiter is optional and defaults to ','.
+    """
+    def load_voice(self, voice: str, delimiter: str = ",") -> torch.FloatTensor:
+        if voice in self.voices:
+            return self.voices[voice]
+        packs = [self.load_single_voice(v) for v in voice.split(delimiter)]
+        if len(packs) == 1:
+            return packs[0]
+        self.voices[voice] = torch.mean(torch.stack(packs), dim=0)
+        return self.voices[voice]
+
     @classmethod
     def waterfall_last(
         cls,