Spoken language understanding (SLU) is a fundamental task in the task-oriented dialogue
systems. However, the inevitable errors from automatic speech recognition (ASR) usually …

Spoken language understanding (SLU) is a critical task in taskoriented dialogue systems.
However, automatic speech recognition (ASR) errors often impair the understanding …

Abstract Language understanding in speech-based systems has attracted extensive interest
from both academic and industrial communities in recent years with the growing demand for …

Spoken language understanding (SLU) is an essential task for machines to understand
human speech for better interactions. However, errors from the automatic speech recognizer …

Spoken language understanding (SLU) inevitably suffers from error propagation from
automatic speech recognition (ASR) in actual scenarios. Some recent works attempt to …

Post-editing in Automatic Speech Recognition (ASR) entails automatically correcting
common and systematic errors produced by the ASR system. The outputs of an ASR system …

Abstract Spoken Language Understanding (SLU), a crucial component of task-oriented
dialogue systems, has consistently garnered attention from both academic and industrial …

Enhancing the robustness towards Automatic Speech Recognition (ASR) errors is of great
importance for Spoken Language Understanding (SLU). Trending ASR-robust SLU systems …

Most existing slot filling models tend to memorize inherent patterns of entities and
corresponding contexts from training data. However, these models can lead to system failure …

With the growing popularity of code-mixed data, there is an increasing need for better
handling of this type of data, which poses a number of challenges, such as dealing with …