diff --git a/wsai/backends/emotion.py b/wsai/backends/emotion.py
index 98a080a..cfe7cd4 100644
--- a/wsai/backends/emotion.py
+++ b/wsai/backends/emotion.py
@@ -23,27 +23,33 @@ from dataclasses import dataclass
 
 # Canonical emotion -> (speed multiplier relative to base, pitch shift in semitones).
 # Kept deliberately modest so delivery stays natural, not cartoonish.
+#
+# Pitch is held at 0.0 for every emotion: librosa's post-hoc pitch_shift on Melo
+# output produced a robotic, "monster"-sounding artefact (worse when stacked on a
+# fast base speed). Emotion is therefore conveyed by speed only — natural and
+# artefact-free. The pitch column is retained (rather than removed) so the effect
+# can be re-enabled per-emotion later with a real, artefact-free pitch method.
 EMOTION_PARAMS: dict[str, tuple[float, float]] = {
-    "happy":       (1.08,  2.0),   # 기쁨 / cheerful
-    "excited":     (1.15,  3.0),   # 신남 / excited
-    "hopeful":     (1.10,  1.5),   # 희망 / 힘차게
-    "sad":         (0.90, -2.5),   # 슬픔 / sad
-    "angry":       (1.12,  1.0),   # 화남 / angry
-    "fearful":     (1.12,  2.0),   # 두려움 / terrified
-    "surprised":   (1.05,  3.0),   # 놀람 / surprise
-    "disgust":     (0.96, -1.0),   # 혐오 / disgust
-    "calm":        (0.95, -1.0),   # 차분 / calm
-    "friendly":    (1.00,  1.0),   # 다정 / friendly
-    "serious":     (0.97, -1.0),   # 진지 / serious
-    "disappointed":(0.92, -2.0),   # 실망 / disappointed
-    "tired":       (0.90, -2.0),   # 피곤 / 지침
-    "affectionate":(0.98,  1.0),   # 사랑스럽게 / affectionate
-    "playful":     (1.08,  2.0),   # 장난스럽게 / playful
-    "whisper":     (0.92, -1.5),   # 속삭임 / whispering
-    "shout":       (1.05,  2.5),   # 외침 / shouting
-    "determined":  (1.05,  0.5),   # 단호 / determined
-    "relieved":    (0.95,  0.5),   # 안도 / relieved
-    "curious":     (1.03,  1.5),   # 궁금 / curious
+    "happy":       (1.08,  0.0),   # 기쁨 / cheerful
+    "excited":     (1.15,  0.0),   # 신남 / excited
+    "hopeful":     (1.10,  0.0),   # 희망 / 힘차게
+    "sad":         (0.90,  0.0),   # 슬픔 / sad
+    "angry":       (1.12,  0.0),   # 화남 / angry
+    "fearful":     (1.12,  0.0),   # 두려움 / terrified
+    "surprised":   (1.05,  0.0),   # 놀람 / surprise
+    "disgust":     (0.96,  0.0),   # 혐오 / disgust
+    "calm":        (0.95,  0.0),   # 차분 / calm
+    "friendly":    (1.00,  0.0),   # 다정 / friendly
+    "serious":     (0.97,  0.0),   # 진지 / serious
+    "disappointed":(0.92,  0.0),   # 실망 / disappointed
+    "tired":       (0.90,  0.0),   # 피곤 / 지침
+    "affectionate":(0.98,  0.0),   # 사랑스럽게 / affectionate
+    "playful":     (1.08,  0.0),   # 장난스럽게 / playful
+    "whisper":     (0.92,  0.0),   # 속삭임 / whispering
+    "shout":       (1.05,  0.0),   # 외침 / shouting
+    "determined":  (1.05,  0.0),   # 단호 / determined
+    "relieved":    (0.95,  0.0),   # 안도 / relieved
+    "curious":     (1.03,  0.0),   # 궁금 / curious
 }
 
 # Every spelling Claude might realistically emit, mapped to a canonical emotion.
diff --git a/wsai/backends/melo.py b/wsai/backends/melo.py
index d1ef5f6..f77a54e 100644
--- a/wsai/backends/melo.py
+++ b/wsai/backends/melo.py
@@ -12,7 +12,7 @@ Env:
     WSAI_MELO_DEVICE   cpu | cuda | auto  (default auto: GPU if torch sees one,
                        else CPU; the worker falls back to CPU if CUDA fails)
     WSAI_TTS_OUT_DIR   where wavs are written (default ~/.cache/wsai/tts)
-    WSAI_TTS_SPEED     synthesis speed multiplier (default 1.3)
+    WSAI_TTS_SPEED     synthesis speed multiplier (default 1.0)
 """
 
 from __future__ import annotations
@@ -93,7 +93,7 @@ class MeloTTS:
         self.out_dir = Path(out_dir or os.environ.get("WSAI_TTS_OUT_DIR")
                             or (Path.home() / ".cache/wsai/tts"))
         self.speed = float(speed if speed is not None
-                           else os.environ.get("WSAI_TTS_SPEED", "1.3"))
+                           else os.environ.get("WSAI_TTS_SPEED", "1.0"))
         self.sink = sink or _log_sink
         self._proc: asyncio.subprocess.Process | None = None
         self._lock = asyncio.Lock()