Editing Hidden Markov Models in Speech Synthesis (section)

==== Emotional Modeling ====
# Emotion-Driven HMM Model: Designing an emotion-driven HMM model that takes emotion tags as input features, enabling the model to adjust synthetic speech characteristics based on emotional information for emotional synthesis. [Mills et al., 2012]<ref>Mills, G., & Schuller, B. W. (2012). [https://ieeexplore.ieee.org/document/6267902/ HMM-based synthesis of emotional speech with multi-formant filter representation]. In Proceedings of the 4th International Workshop on Emotion Corpora and Recognition (pp. 9-14).</ref>
# Modeling Emotion in a Multidimensional Space: Treating emotion as a multi-dimensional space and synthesizing different emotions by modeling speech feature distribution in this space. [Schuller et al., 2003]<ref>Schuller, B., Batliner, A., Seppi, D., Steidl, S., Vogt, T., Wagner, J., ... & Devillers, L. (2003). [https://ieeexplore.ieee.org/document/1234102/ The relevance of feature type for the automatic classification of emotional user states: Low level descriptors and functionals]. In European Conference on Speech Communication and Technology.</ref>