Real to H-Space Autoencoders for Theme Identification in Telephone Conversations

• Published in: IEEE/ACM transactions on audio, speech, and language processing Vol. 28; pp. 198 - 210
• Main Authors: Parcollet, Titouan, Morchid, Mohamed, Bost, Xavier, Linares, Georges, De Mori, Renato
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Artificial neural networks; Computer Science; Customer services; Feature extraction; Features extraction; Machine learning; Neural networks; Parameters; Performance enhancement; quaternion autoencoder; quaternion neural networks; Quaternions; Semantics; Signal processing; Speech recognition; spoken language understanding; Task analysis; Telephone sets; Voice recognition; Index Terms-Features extraction; spoken language understanding; quaternion autoencoder; quaternion neural networks

Machine learning (ML) and deep learning with deep neural networks (DNN), have drastically improved the performances of modern systems on numerous spoken language understanding (SLU) related tasks. Since most of current researches focus on new neural architectures to enhance the performances in reali...