@telegram_bot.message_handler(content_types=["voice"])
def audio_processing(message: Any) -> None:
    assistant.process_voice_message(message)

def process_voice_message(self, message: Any) -> None:
    # 1. Скачать OGG-файл из Telegram
    file_info   = self.bot.get_file(message.voice.file_id)
    voice_bytes = self.bot.download_file(file_info.file_path)

    # 2. Транскрибировать через Groq Whisper-large-v3
    transcription  = self.voice_service.transcribe_telegram_voice(voice_bytes)
    recognized_text = metadata_value(transcription, "text", "").strip()

    # 3. Фильтр нераспознанной речи (4 порога)
    if is_unintelligible_transcription(transcription):
        self.bot.send_message(message.from_user.id, UNINTELLIGIBLE_VOICE_MESSAGE)
        return

    # 4. Передать в AI-цепочку (n8n → DeepSeek → ответ)
    self._process_user_request(message.from_user.id, recognized_text)

NO_SPEECH_PROB_THRESHOLD          = 0.6   # вероятность тишины > 60%
LOW_CONFIDENCE_AVG_LOGPROB         = -1.0  # низкая уверенность модели
NO_SPEECH_SEGMENT_RATIO_THRESHOLD = 0.5   # доля «тихих» сегментов

def is_unintelligible_transcription(transcription: Any) -> bool:
    segments        = transcription.segments or []
    no_speech_probs = [s.no_speech_prob for s in segments]
    avg_logprobs    = [s.avg_logprob     for s in segments]

    mean_nsp   = _mean(no_speech_probs)
    mean_logp  = _mean(avg_logprobs)
    bad_ratio  = _ratio_at_least(no_speech_probs, NO_SPEECH_PROB_THRESHOLD)

    return (
        mean_nsp  >= NO_SPEECH_PROB_THRESHOLD          # порог 1
        or bad_ratio >= NO_SPEECH_SEGMENT_RATIO_THRESHOLD # порог 2
        or mean_logp  <= LOW_CONFIDENCE_AVG_LOGPROB       # порог 3
        or not transcription.text.strip()                 # порог 4
    )