Speech spectrum transformation by speaker interpolation

Proposes a speech spectrum transformation method by interpolating spectral patterns between pre-stored multiple speakers for speech synthesis. The interpolation is carried out using spectral parameters such as cepstrum and log area ratio to generate new spectrum patterns. The spectral patterns can be transformed smoothly as the interpolation ratio is gradually changed, and speech individuality can easily be controlled between interpolated speakers. Adaptation to a target speaker can be performed by this interpolation, which uses only a small amount of training data to generate a new speech spectrum sequence close to the target speaker´s. An adaptation experiment was carried out in the case of using only one word spoken by the target speaker for learning. It was shown that the distance between the target speaker´s spectrum and the spectrum generated by the proposed interpolation method is reduced by about 40% compared with distance between the target speaker´s spectrum and spectrum of the speaker closest to the target among pre-stored ones