Automatic concept extraction from spoken medical reports.
OBJECTIVE
The objective of this project is to investigate methods whereby a combination of speech recognition and automated indexing methods substitute for current transcription and indexing practices.


METHODS
We based our study on existing speech recognition software programs and on NOMINDEX, a tool that extracts MeSH concepts from medical text in natural language and that is mainly based on a French medical lexicon and on the UMLS. For each document, the process consists of three steps: (1) dictation and digital audio recording, (2) speech recognition, (3) automatic indexing. The evaluation consisted of a comparison between the set of concepts extracted by NOMINDEX after the speech recognition phase and the set of keywords manually extracted from the initial document. The method was evaluated on a set of 28 patient discharge summaries extracted from the MENELAS corpus in French, corresponding to in-patients admitted for coronarography.


RESULTS
The overall precision was 73% and the overall recall was 90%. Indexing errors were mainly due to word sense ambiguity and abbreviations. A specific issue was the fact that the standard French translation of MeSH terms lacks diacritics. A preliminary evaluation of speech recognition tools showed that the rate of accurate recognition was higher than 98%. Only 3% of the indexing errors were generated by inadequate speech recognition.


CONCLUSIONS
We discuss several areas to focus on to improve this prototype. However, the very low rate of indexing errors due to speech recognition errors highlights the potential benefits of combining speech recognition techniques and automatic indexing.
Happe
André
A
Intermède, La Basse Revachais, 35580 Guignen, France. happe@intermede.net
Pouliquen
Bruno
B
Burgun
Anita
A
Cuggia
Marc
M
Le Beux
Pierre
P
D000043:Abstracting and Indexing; D001185:Artificial Intelligence; D004282:Documentation; D006801:Humans; D016347:Medical Records Systems, Computerized / Q000592:standards*; D009323:Natural Language Processing; D015203:Reproducibility of Results; D012984:Software; D013060:Speech; D009626:Terminology as Topic; D017432:Unified Medical Language System; D014584:User-Computer Interface; D014831:Voice