Abstract
With the increasing interest in Spoken Language Understanding (SLU) related applications such as voice assistant and automated answering system, we aim to find a better system solution for such tasks, in particular, concentrating on the semantic parsing procedure that transforms the spoken language into a Meaning Representation Language (MRL) where only the semantic meaning and logistic relations in the word span are preserved. The viability of the stage in SLU known as "grounding" between our proposed MRL, Abstract Meaning Representation (AMR) language, and computer- interpretable commands is also analyzed in this thesis. To assist with the planned experiments, the first AMR corpus that is populated with spoken language transcription is created by manual annotation, providing as a reference for future studies on SLU- oriented AMR parsing tasks.