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@@ -116,7 +116,10 @@ class STTSink(Sink):
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continue # ✅ PAS return
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if reply_mode == ReplyMode.TEXT and reply_text_channel:
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- await reply_text_channel.send(f"🗣️ {text}")
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+ member = reply_text_channel.guild.get_member(user_id)
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+ name = member.display_name if member else f"User {user_id}"
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+
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+ await reply_text_channel.send(f"🗣️ **{name}** : {text}")
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else:
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logger.info(f"[STT][{user_id}] {text}")
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@@ -188,21 +191,22 @@ class STTSink(Sink):
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conversation_history = []
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def discord_pcm_to_whisper_int16(pcm_bytes: bytes) -> bytes:
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- # PCM 48 kHz int16 -> numpy
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- audio_48k = np.frombuffer(pcm_bytes, dtype=np.int16)
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- if audio_48k.size == 0:
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- return b""
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+ audio = np.frombuffer(pcm_bytes, dtype=np.int16).astype(np.float32)
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+
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+ # normalisation RMS
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+ rms = np.sqrt(np.mean(audio**2) + 1e-8)
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+ audio = audio / max(rms, 5000)
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- # int16 -> float32 pour resample
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- audio_float32 = audio_48k.astype(np.float32) / 32768.0
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+ # passe-bas léger avant downsample
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+ audio = audio / 32768.0
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- # resample 48kHz -> 16kHz
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- audio_16k = resample_poly(audio_float32, up=1, down=3)
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+ # resample 48k → 16k
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+ audio_16k = resample_poly(audio, up=1, down=3, window=('kaiser', 5.0))
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- # float32 -> int16 (CE QUE WHISPER ATTEND)
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- audio_16k_int16 = np.clip(audio_16k * 32768.0, -32768, 32767).astype(np.int16)
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+ # clip sécurité
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+ audio_16k = np.clip(audio_16k, -1.0, 1.0)
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- return audio_16k_int16.tobytes()
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+ return (audio_16k * 32767).astype(np.int16).tobytes()
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def filter_message(message):
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"""Filtre le contenu d'un retour de modèle de language, comme pour enlever les pensées dans le cas par exemple de DeepSeek"""
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