diff --git a/server/const.py b/server/const.py
index 428b0439..89338d64 100644
--- a/server/const.py
+++ b/server/const.py
@@ -87,6 +87,7 @@ class EnumInferenceTypes(Enum):
 class EnumPitchExtractorTypes(Enum):
     harvest = "harvest"
     dio = "dio"
+    crepe = "crepe"
 
 
 class EnumFrameworkTypes(Enum):
diff --git a/server/voice_changer/RVC/pitchExtractor/CrepePitchExtractor.py b/server/voice_changer/RVC/pitchExtractor/CrepePitchExtractor.py
new file mode 100644
index 00000000..14d5a112
--- /dev/null
+++ b/server/voice_changer/RVC/pitchExtractor/CrepePitchExtractor.py
@@ -0,0 +1,47 @@
+import torchcrepe
+import torch
+import numpy as np
+
+from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
+
+
+class CrepePitchExtractor(PitchExtractor):
+    def __init__(self):
+        super().__init__()
+        if torch.cuda.is_available():
+            self.device = torch.device('cuda:' + str(torch.cuda.current_device()))
+        else:
+            self.device = torch.device('cpu')
+        
+    def extract(self, audio, f0_up_key, sr, window, silence_front=0):
+        n_frames = int(len(audio) // window) + 1
+        start_frame = int(silence_front * sr / window)
+        real_silence_front = start_frame * window / sr
+
+        silence_front_offset = int(np.round(real_silence_front * sr))
+        audio = audio[silence_front_offset:]
+
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+
+        f0 = torchcrepe.predict(torch.tensor(audio).unsqueeze(0), sr,
+                hop_length=window, fmin=f0_min, fmax=f0_max, model='tiny', batch_size=256,
+                decoder=torchcrepe.decode.weighted_argmax, device=self.device)
+        f0 = f0.squeeze().detach().cpu().numpy()
+
+        f0 = np.pad(f0.astype("float"), (start_frame, n_frames - f0.shape[0] - start_frame))
+
+        f0 *= pow(2, f0_up_key / 12)
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int)
+
+        return f0_coarse, f0bak
+
diff --git a/server/voice_changer/RVC/pitchExtractor/PitchExtractorManager.py b/server/voice_changer/RVC/pitchExtractor/PitchExtractorManager.py
index 3c4ab1e2..8992d81e 100644
--- a/server/voice_changer/RVC/pitchExtractor/PitchExtractorManager.py
+++ b/server/voice_changer/RVC/pitchExtractor/PitchExtractorManager.py
@@ -2,6 +2,7 @@ from typing import Protocol
 from const import EnumPitchExtractorTypes
 from voice_changer.RVC.pitchExtractor.DioPitchExtractor import DioPitchExtractor
 from voice_changer.RVC.pitchExtractor.HarvestPitchExtractor import HarvestPitchExtractor
+from voice_changer.RVC.pitchExtractor.CrepePitchExtractor import CrepePitchExtractor
 from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
 
 
@@ -29,6 +30,11 @@ class PitchExtractorManager(Protocol):
             or pitchExtractorType == EnumPitchExtractorTypes.dio.value
         ):
             return DioPitchExtractor()
+        elif (
+            pitchExtractorType == EnumPitchExtractorTypes.crepe
+            or pitchExtractorType == EnumPitchExtractorTypes.crepe.value
+        ):
+            return CrepePitchExtractor()
         else:
             # return hubert as default
             raise RuntimeError(