{"type":"ScholarlyArticle","title":"Alignment Algorithms for Learning to Read Aloud","authors":[{"name":"Charles X. Ling","slug":"charles-x-ling","given":"Charles X.","family":"Ling","affiliation":""},{"name":"Handong Wang","slug":"handong-wang","given":"Handong","family":"Wang","affiliation":""}],"abstract":"A complete system of learning spelling-tophoneme conversion of English words consists of three major processes: alignment, mapping learning, and grapheme generation. Such a system can be used to construct prototypes of reading machines for English or other languages quickly and automatically. ~his. pap.er focusses on the alignment process, which IS cntical to mapping learning and grapheme generation. We present several novel alignment algorithms which learn alignment without supervision. The basic alignment algorithm is a hillclimbing algorithm. Several improvements of it are studied and tested. In addition, a method that overcomes the pitfall in hill-climbing algorithms is designed. Our best alignment algorithm produces very impressive results: only 0.5% of error rate.","doi":null,"url":"https://ijcai.org/proceedings/1997/126","pdf":"https://ijcai.org/proceedings/1997/0126.pdf","markdown":"https://ijcai.org/proceedings/1997/126.md","bibtex":"https://ijcai.org/proceedings/1997/bibtex/126","volume":{"slug":"1997","title":"Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1997","url":"https://ijcai.org/proceedings/1997/","year":1997,"location":"Nagoya, Japan","dates":"","editors":"Martha E. Pollack","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Learning","track":"Learning","number":126,"pages":{"first":874,"last":878},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}