diff --git a/scripts/tts_pytorch.py b/scripts/tts_pytorch.py
index e95c563..0e6e6dc 100644
--- a/scripts/tts_pytorch.py
+++ b/scripts/tts_pytorch.py
@@ -4,17 +4,37 @@
 #     "moshi @ git+https://git@github.com/kyutai-labs/moshi#egg=moshi&subdirectory=moshi",
 #     "torch",
 #     "sphn",
+#     "sounddevice",
 # ]
 # ///
 import argparse
 import sys
 
+import numpy as np
 import sphn
 import torch
 from moshi.models.loaders import CheckpointInfo
 from moshi.models.tts import DEFAULT_DSM_TTS_REPO, DEFAULT_DSM_TTS_VOICE_REPO, TTSModel
 
 
+def audio_to_int16(audio: np.ndarray) -> np.ndarray:
+    if audio.dtype == np.int16:
+        return audio
+    elif audio.dtype == np.float32:
+        # Multiply by 32767 and not 32768 so that int16 doesn't overflow.
+        return (np.clip(audio, -1, 1) * 32767).astype(np.int16)
+    else:
+        raise TypeError(f"Unsupported audio data type: {audio.dtype}")
+
+
+def play_audio(audio: np.ndarray, sample_rate: int):
+    # Requires the Portaudio library which might not be available in all environments.
+    import sounddevice as sd
+
+    with sd.OutputStream(samplerate=sample_rate, blocksize=1920, channels=1):
+        sd.play(audio, sample_rate)
+
+
 def main():
     parser = argparse.ArgumentParser(
         description="Run Kyutai TTS using the PyTorch implementation"
@@ -49,7 +69,8 @@ def main():
     )
 
     if args.inp == "-":
-        print("Enter text to synthesize (Ctrl+D to end input):")
+        if sys.stdin.isatty():  # Interactive
+            print("Enter text to synthesize (Ctrl+D to end input):")
         text = sys.stdin.read().strip()
     else:
         with open(args.inp, "r") as fobj:
@@ -73,8 +94,12 @@ def main():
     with torch.no_grad():
         audios = tts_model.mimi.decode(audio_tokens)
 
-    sphn.write_wav(args.out, audios[0].cpu().numpy(), tts_model.mimi.sample_rate)
-    print(f"Audio saved to {args.out}")
+    if args.out == "-":
+        print("Playing audio...")
+        play_audio(audios[0][0].cpu().numpy(), tts_model.mimi.sample_rate)
+    else:
+        sphn.write_wav(args.out, audios[0].cpu().numpy(), tts_model.mimi.sample_rate)
+        print(f"Audio saved to {args.out}")
 
 
 if __name__ == "__main__":