Acusis Medical Transcription Services- Company Overview

<%@LANGUAGE="VBSCRIPT" CODEPAGE="1252"%> Acusis Medical Transcription Services- Company Overview

Transcription on Demand

An important part of our success is technology and we continually look for ways to better support our customers and internal users. To stay on the cutting edge and deliver the highest quality – accurate and timely transcripts – we collaborate with leading research institutions and have internal research and software development resources. In addition,
Acusis has established a technology Advisory Board whose focus is on selected technical areas that are core to our technology strategy.

Acusis Advanced Technology is a dedicated team exploring novel technologies as well as creative uses of existing technologies that can help us further improve quality and turnaround time in a cost-effective and user-friendly way. In addition, we have a large software development team to implement and deploy the most promising ideas into our production and customer systems.

Focus Areas
Medical transcription used to be considered a low technology domain, but not any more. At Acusis, we are actively investigating how signal processing, speech and language technologies can be effectively deployed to maintain and further improve quality and turnaround time. Our current activities include:

	Human Language Technologies
	Speech Recognition Natural Language Processing Statistical Language Modeling
	Signal Processing
	Human Factors

Medical transcription is about converting medical dictation into structured, searchable information, and human language technologies (HLT) plays increasingly important role in this process. We have three such technologies under development at Acusis: Automated speech recognition (ASR), Natural Language Processing (NLP) and Statistical Language Modeling (SLM).

While ASR will not be able to replace human transcriptionists in a foreseeable future, we are exploring how it can augment human capabilities to improve quality and turnaround time. Language modeling is used in ASR, but it also has potential on its own. We are exploring how SLM, in combination with NLP, can provide context-sensitive error detection. Another important area is providing smart information extraction capabilities to add value to customer reports.

Regardless of whether ASR is used or not, the audio quality is an important factor affecting transcription quality. While we cannot always control the dictation environment and habits of our speakers, signal processing techniques can help us improve the audio, reduce transcriptionists’ fatigue and improve accuracy.

Human factors and task analysis are ongoing activities aimed at further improving usability of our transcription platform and overall user experience, for both our internal users and our customers.

Advisory Board
Acusis trusts in the breakthrough role technology will play in the medical transcription domain, and has established a technology Advisory Board of leading experts in selected technical areas that are core to our technology strategy.

Current board members are

Bill Benter

Bill Benter is a Chairman & International CEO of Acusis. Before creating Acusis, Benter had a career in high technology entrepreneurial software development. A recognized expert in mathematical modeling, probability theory and statistical analysis, he has been invited speaker and lecturer at Stanford University, City University of Hong Kong and other universities and international conferences, and a published author. Benter has lectured on theoretical and practical aspects of creating empirically derived mathematical models and on applying advanced computer based statistical techniques to real-world problems. Mr. Benter was born and raised in Pittsburgh, Pennsylvania and studied at Case Western Reserve, University of Bristol (England), and the University of Pittsburgh. He is an enthusiastic and long-term Rotary Club member who follows the Rotary model of "Service above Self"

Kathleen R.
McKeown

Kathleen R. McKeown is a Professor of Computer Science at Columbia University . Her research interests include text summarization, natural language generation, multi-media explanation, digital libraries, concept to speech generation and natural language interfaces. McKeown received the Ph.D. in Computer Science from the University of Pennsylvania in 1982 and has been at Columbia since then. In 1985 she received a National Science Foundation Presidential Young Investigator Award, in 1991 she received a National Science Foundation Faculty Award for Women, and in 1994 was selected as an AAAI Fellow. McKeown serves as a board member of the Computing Research Association. Previously. she served as President of the Association of Computational Linguistics in 1992, Vice President in 1991, and Secretary Treasurer for 1995-1997. She has also served on the Executive Council of the Association for Artificial Intelligence and was co-program chair of their annual conference in 1991.

Roni Rosenfeld

Roni Rosenfeld is Professor of Language Technologies, Machine Learning and Computer Science at the School of Computer Science , Carnegie Mellon University in Pittsburgh , Pennsylvania . He received a B.Sc. degree in Mathematics and Physics from Tel-Aviv University in 1985, a Masters degree in Computer Science from Carnegie Mellon in 1990, and a Ph.D. in Computer Science from Carnegie Mellon in 1994. He is a National Science Foundation Graduate Fellow, and a recipient of the Allen Newell Medal for Research Excellence. Professor Rosenfeld's current research interests are in computational molecular biology, molecular evolution, human-machine speech communication, and the use of speech and language technologies to aid international development. He has also performed research in statistical language modeling, machine learning and speech recognition. He has published over 100 scientific articles in academic journals and conferences.

Richard Stern

Richard Stern is a Professor of Electrical Engineering and Computer Science at Carnegie Mellon University , where he has been a member of the faculty since 1977. He received his Ph.D. in electrical engineering from the Massachusetts Institute of Technology (MIT), after receiving a Bachelor's Degree from MIT and a Masters from the University of California , Berkeley .

Much of Dr. Stern's current research is in spoken language systems, where he is particularly concerned with the development of techniques for making automatic speech recognition more robust with respect to changes in environment and acoustical ambience. He also maintains an active research program in auditory perception, where he is best known for theoretical work in binaural hearing.

Dr. Stern has served on numerous technical and standards committees for the IEEE and for the Defense Advanced Research Projects Agency (DARPA). He is the General Chair of the International Conference on Spoken Language Processing to be held in Pittsburgh in September 2006, sponsored by the International Speech Communication Association. Dr. Stern is a member of the IEEE, the Acoustical Society of America, and the Audio Engineering Society. He was a recipient of the Allen Newell Award for Research Excellence in 1992.