Abstract
Purpose:The purpose of this study is to build a routine nursing record corpus and evaluate the feasibility of using speech recognition in nursing record. Methods:We selected electronic nursing record from a medicalcenter in Taiwan as text training data. The data were recorded during Jul, 07 to Mar, 08, included 7 ICU wards and 5 general wards. We used word segmentation and unknown-word extraction system from ACADEMIA SINICA to extract nursing record lexicon and training language models with and without the new lexicon, thencalculate the perplexity of language models as evaluation. Results:This study accomplishes 1,000,000 nursing record corpus and 974 words nursing record lexicon. The relative perplexity reduction is 15.541％ from themodel without nursing record lexicon to the model with 974-words nursing record lexicon. Conclusions:According to rule of thumb, the influence of nursing records lexicon on the speech recognition is noteworthy.
| Translated title of the contribution | Building a Routine Nursing Records Corpus, Lexicon andIts Application in the Speech Recognition |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 25-35 |
| Journal | 醫療資訊雜誌 |
| Volume | 20 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2011 |