nnmnkwii.metrics.lf0_mean_squared_error¶
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nnmnkwii.metrics.lf0_mean_squared_error(src_f0, src_vuv, tgt_f0, tgt_vuv, lengths=None, linear_domain=False)[source]¶ Mean squared error (MSE) for log-F0 sequences.
MSE is computed for voiced segments.
- Parameters
src_f0 (ndarray) – Input log-F0 sequences, shape can be either of (
T,), (B x T) or (B x T x 1). Both Numpy and torch arrays are supported.src_vuv (ndarray) – Input voiced/unvoiced flag array, shape can be either of (
T, ), (B x T) or (B x T x 1).tgt_f0 (ndarray) – Target log-F0 sequences, shape can be either of (
T,), (B x T) or (B x T x 1). Both Numpy and torch arrays are supported.tgt_vuv (ndarray) – Target voiced/unvoiced flag array, shape can be either of (
T, ), (B x T) or (B x T x 1).lengths (list) – Lengths of padded inputs. This should only be specified if you give mini-batch inputs.
linear_domain (bool) – Whether computes MSE on linear frequecy domain or log-frequency domain.
- Returns
mean squared error.
- Return type