Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders

no code implementations • WS 2017 • Tsuneo Kato, Atsushi Nagai, Naoki Noda, Ryosuke Sumitomo, Jianming Wu, Seiichi Yamamoto

Recursive autoencoders (RAEs) for compositionality of a vector space model were applied to utterance intent classification of a smartphone-based Japanese-language spoken dialogue system.

Automatic Speech Recognition (ASR) Classification +5