Learning speaker normalization using semisupervised manifold alignment

As a child acquires language, he or she: perceives acoustic information in his or her surrounding environment; identifies portions of the ambient acoustic information as languagerelated; and associates that language-related information with his or her perception of his or her own language-related acoustic productions. The present work models the third task. We use a semisupervised alignment algorithm based on manifold learning. We discuss the concepts behind this approach, and the application of the algorithm to this task. We present experimental evidence indicating the usefulness of manifold alignment in learning speaker normalization.

• Type: Journal
• Year: 2010
• Where: INTERSPEECH
• Authors: Andrew R. Plummer, Mary E. Beckman, Mikhail Belkin, Eric Fosler-Lussier, Benjamin Munson
• Keywords: Acoustic Information, Ambient Acoustic Information, INTERSPEECH 2010, Language-related Acoustic Productions, Signal Processing