def denoise_audio_segment()

in src/diarizers/data/synthetic_pipeline.py [0:0]

• 14 lines of code
• 1 McCabe index (conditional complexity)

    def denoise_audio_segment(self, audio_file, rank=None):
        """Denoise input audio.

        Args:
            audio_file (np.ndarray): generated meeting audio array.

        Returns:
            audio_file (np.ndarray): denoised generated meeting audio array.
        """

        device = f"cuda:{(rank or 0)% torch.cuda.device_count()}"
        self.denoiser = self.denoiser.to(device)

        audio_file_converted = convert_audio(
            torch.tensor(audio_file).unsqueeze(0).to(device),
            self.sample_rate,
            self.denoiser.sample_rate,
            self.denoiser.chin,
        )
        with torch.no_grad():
            audio_file = (
                self.denoiser(torch.tensor(audio_file_converted, dtype=torch.float32))[0].squeeze(0).cpu().numpy()
            )
        return audio_file