Towards Cross-Lingual Emotion Transplantation

In this paper we introduce the idea of cross-lingual emotion transplantation. The aim is to lean the nuances of emotional speech in a source language for which we have enough data to adapt an acceptable quality emotional model by means of CSMAPLR adaptation, and then convert the adaptation function so it can be applied to a target language in a different target speaker while maintaining the speaker identity but adding emotional information. The conversion between languages is done at state level by measuring the KLD distance between the Gaussian distributions of all the states and linking the closest ones. Finally, as the cross-lingual transplantation of spectral emotions (mainly anger) was found out to introduce significant amounts of spectral noise, we show the results of applying three different techniques related to adaptation parameters that can be used to reduce the noise. The results are measured in an objective fashion by means of a bi-dimensional PCA projection of the KLD distances between the considered models (neutral models of both languages, reference emotion for both languages and transplanted emotional model for the target language).