Sixth International Conference on Spoken Language Processing
In this paper, we report our semantic tagging tool for spoken dialogue corpus. This tagging tool can acquire analysis rules using Transformation-based Learning (TBL) from small scale training corpus. It can learn dialogue act tagging rules and semantic frame tagging rules. The precisions are 72% in dialogue act tagging and 58% of semantic frame tagging in open test.
Bibliographic reference. Araki, Masahiro / Ueda, Kiyoshi / Nishimoto, Takuya / Niimi, Yasuhisa (2000): "A semantic tagging tool for spoken dialogue corpus", In ICSLP-2000, vol.4, 720-723.