def METHOD_NAME(barks: torch.Tensor, bark_scale: str = "traunmuller") -> torch.Tensor:
    """Convert bark bin numbers to frequencies.
    Args:
        barks (torch.Tensor): Bark frequencies
        bark_scale (str, optional): Scale to use: ``traunmuller``,``schroeder`` or ``wang``. (Default: ``traunmuller``)
    Returns:
        freqs (torch.Tensor): Barks converted in Hz
    """
    if bark_scale not in ["schroeder", "traunmuller", "wang"]:
        raise ValueError('bark_scale should be one of "traunmuller", "schroeder" or "wang".')
    if bark_scale == "wang":
        return 600.0 * torch.sinh(barks / 6.0)
    elif bark_scale == "schroeder":
        return 650.0 * torch.sinh(barks / 7.0)
    # Bark value correction
    if any(barks < 2):
        idx = barks < 2
        barks[idx] = (barks[idx] - 0.3) / 0.85
    elif any(barks > 20.1):
        idx = barks > 20.1
        barks[idx] = (barks[idx] + 4.422) / 1.22
    # Traunmuller Bark scale
    freqs = 1960 * ((barks + 0.53) / (26.28 - barks))
    return freqs