def METHOD_NAME(phoneme_count: int, mel_count: int, scaling_factor: float = 1.0) -> np.array:
    x = rearrange(torch.arange(0, phoneme_count), "b -> 1 b")
    y = rearrange(torch.arange(1, mel_count + 1), "b -> b 1")
    a = scaling_factor * y
    b = scaling_factor * (mel_count + 1 - y)
    n = torch.FloatTensor([phoneme_count - 1])
    return logbetabinom(n, a, b, x).exp().numpy()