@article{oai:kindai.repo.nii.ac.jp:00014986,
 author = {勝瀬,  郁代 and MASUDA-KATSUSE, Ikuyo},
 issue = {2},
 journal = {かやのもり：近畿大学産業理工学部研究報告, Reports of Faculty of Humanity-Oriented Science and Engineering, Kinki University},
 month = {Nov},
 note = {A new automatic speech recognition (ASR) method, PHONOBEST, is proposed, aiming to achieve robust ASR in a real environment. In ASRs, we need to compare observed speech with template speech in the pattern matching process. Such template speech can be regarded as a kind of top-down information generated from speech schema. In human speech perception, the top-down process seems to work more than preparing candidates for pattern matching. It also seems to predispose the segregation process to extract an object agreeing with the "expectation" generated by speech schema. PHONOBEST has introduced this active bias into the process of target speech estimation. A missing­data model is also implemented in PHONOBEST by using fine spectral representation with harmonic structures as template patterns; on the other hand, the spectral envelopes are supplied as template patterns in the prevailing ASRs. In this paper, the current status and remaining assignments are discussed.},
 pages = {9--17},
 title = {音韻知識にバイアスされた音韻推定：PHONOBEST～現状と残された課題～},
 volume = {7},
 year = {2007},
 yomi = {カツセ, イクヨ}
}