diff --git a/CHANGELOG.md b/CHANGELOG.md
index c381ac630..f6debb3b3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -13,6 +13,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Added `VADParams` so you can control voice confidence level and others.
 
+- `VADAnalyzer` now uses an exponential smoothing to avoid sudden changes.
+
 ### Fixed
 
 - Fixed issues with Ctrl-C program termination.
diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py
index c1cba90a7..67c2eddc9 100644
--- a/examples/foundational/07-interruptible.py
+++ b/examples/foundational/07-interruptible.py
@@ -28,7 +28,7 @@ from dotenv import load_dotenv
 load_dotenv(override=True)
 
 logger.remove(0)
-logger.add(sys.stderr, level="TRACE")
+logger.add(sys.stderr, level="DEBUG")
 
 
 async def main(room_url: str, token):
diff --git a/src/pipecat/vad/vad_analyzer.py b/src/pipecat/vad/vad_analyzer.py
index 6c4afceba..23f7263ab 100644
--- a/src/pipecat/vad/vad_analyzer.py
+++ b/src/pipecat/vad/vad_analyzer.py
@@ -20,7 +20,7 @@ class VADState(Enum):
 
 
 class VADParams(BaseModel):
-    confidence: float = 0.8
+    confidence: float = 0.6
     start_secs: float = 0.2
     stop_secs: float = 0.8
 
@@ -43,6 +43,10 @@ class VADAnalyzer:
 
         self._vad_buffer = b""
 
+        # Exponential smoothing
+        self._smoothing_factor = 0.6
+        self._prev_confidence = 1 - self._smoothing_factor
+
     @property
     def sample_rate(self):
         return self._sample_rate
@@ -55,6 +59,11 @@ class VADAnalyzer:
     def voice_confidence(self, buffer) -> float:
         pass
 
+    def _smoothed_confidence(self, audio_frames, prev_confidence, factor):
+        confidence = self.voice_confidence(audio_frames)
+        smoothed = exp_smoothing(confidence, prev_confidence, factor)
+        return smoothed
+
     def analyze_audio(self, buffer) -> VADState:
         self._vad_buffer += buffer
 
@@ -65,7 +74,10 @@ class VADAnalyzer:
         audio_frames = self._vad_buffer[:num_required_bytes]
         self._vad_buffer = self._vad_buffer[num_required_bytes:]
 
-        confidence = self.voice_confidence(audio_frames)
+        confidence = self._smoothed_confidence(
+            audio_frames, self._prev_confidence, self._smoothing_factor)
+        self._prev_confidence = confidence
+
         speaking = confidence >= self._params.confidence
 
         if speaking: