Semantic and phonetic automatic reconstruction of medical dictations
نویسندگان
چکیده
منابع مشابه
Semantic and phonetic automatic reconstruction of medical dictations
Automatic speech recognition (ASR) has become a valuable tool in large document production environments like medical dictation. While manual post-processing is still needed for correcting speech recognition errors and for creating documents which adhere to various stylistic and formatting conventions, a large part of the document production process is carried out by the ASR system. For improvin...
متن کاملSemantics-based Automatic Literal Reconstruction Of Dictations
This paper describes a method for the automatic literal reconstruction of dictations in the domain of medical reports. The raw output of an automatic speech recognition system and the final report edited by a professional medical transcriptionist serve as input to the reconstruction algorithm. Reconstruction is based on automatic alignment between the speech recognition result and the edited re...
متن کاملGenerating Training Data for Medical Dictations
In automatic speech recognition (ASR) enabled applications for medical dictations, corpora of literal transcriptions of speech are critical for training both speaker independent and speaker adapted acoustic models. Obtaining these transcriptions is both costly and time consuming. Non-literal transcriptions, on the other hand, are easy to obtain because they are generated in the normal course of...
متن کاملModeling Filled Pauses in Medical Dictations
Filled pauses are characteristic of spontaneous speech and can present considerable problems for speech recognition by being often recognized as short words. An um can be recognized as thumb or arm if the recognizer's language model does not adequately represent FP's. Recognition of quasi-spontaneous speech (medical dictation) is subject to this problem as well. Results from medical dictations ...
متن کاملIdentifying Segment Topics in Medical Dictations
In this paper, we describe the use of lexical and semantic features for topic classification in dictated medical reports. First, we employ SVM classification to assign whole reports to coarse work-type categories. Afterwards, text segments and their topic are identified in the output of automatic speech recognition. This is done by assigning work-type-specific topic labels to each word based on...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Speech & Language
سال: 2011
ISSN: 0885-2308
DOI: 10.1016/j.csl.2010.07.003