spoken language understanding

SLUE: NEW BENCHMARK TASKS FOR SPOKEN LANGUAGE UNDERSTANDING EVALUATION ON NATURAL SPEECH

TOWARDS REDUCING THE NEED FOR SPEECH TRAINING DATA TO BUILD SPOKEN LANGUAGE UNDERSTANDING SYSTEMS

TOWARDS END-TO-END INTEGRATION OF DIALOG HISTORY FOR IMPROVED SPOKEN LANGUAGE UNDERSTANDING

A BERT based Joint Learning Model with Feature Gated Mechanism for Spoken Language Understanding

IMPROVING SPOKEN LANGUAGE UNDERSTANDING BY ENHANCING TEXT REPRESENTATION

MULTI-TASK RNN-T WITH SEMANTIC DECODER FOR STREAMABLE SPOKEN LANGUAGE UNDERSTANDING

TINYS2I: A SMALL-FOOTPRINT UTTERANCE CLASSIFICATION MODEL WITH CONTEXTUAL SUPPORT FOR ON-DEVICE SLU

A GRAPH ATTENTION INTERACTIVE REFINE FRAMEWORK WITH CONTEXTUAL REGULARIZATION FOR JOINTING INTENT DETECTION AND SLOT FILLING

SLIM: EXPLICIT SLOT-INTENT MAPPING WITH BERT FOR JOINT MULTI-INTENT DETECTION AND SLOT FILLING

LEVERAGING BILINEAR ATTENTION TO IMPROVE SPOKEN LANGUAGE UNDERSTANDING

ESPNET-SLU: ADVANCING SPOKEN LANGUAGE UNDERSTANDING THROUGH ESPNET

TIE YOUR EMBEDDINGS DOWN: CROSS-MODAL LATENT SPACES FOR END-TO-END SPOKEN LANGUAGE UNDERSTANDING