the aim is to enable more robust and accurate speech comprehension in diverse real-life scenarios.
Recent studies, including the comprehensive analysis of the performance of different models
and techniques for Keyword Spotting (KS) and Slot Filling (SF) tasks on Google Speech Commands
and ATIS benchmark datasets (Table 12), have furnished valuable insights into the strengths and
limitations of such approaches in SLU. Capitalizing on these findings and leveraging the latest
advances in deep learning and speech recognition could help us continue to expand the frontiers of
spoken language understanding and drive further innovation in this domain.
AReviewofDeepLearningTechniquesforSpeechProcessing