A data-driven method for input feature selection within neural prosody generation
Çağlayan Erdem, Hans-Georg Zimmermann · IEEE International Conference on Acoustics Speech and Signal Processing · 2002
The analysis and selection of input features within machine learning techniques is an important problem if a new system has to be established or the system has to be trained for a new task. Within a Text-to-Speech (ITS) application this task has to be handled while adapting a system to a new language or a new speaker.