scholarly journals Towards Semi-Automatic Analysis of Spontaneous Language for Dutch

2021 ◽  
Author(s):  
Jan Odijk
Keyword(s):  
Automatic Analysis ◽  
Spontaneous Language

The wheat and the chaff: or four confusions regarding CHILDES

1992 ◽  
Vol 19 (2) ◽  
pp. 459-471 ◽  
Author(s):  
Brian Macwhinney ◽  
Catherine Snow
Keyword(s):  
Data Analysis ◽  
Data Exchange ◽  
Child Language ◽  
Automatic Analysis ◽  
Exchange System ◽  
Spontaneous Language ◽  
Language Data ◽  
Rigid Set

ABSTRACTEdwards (1992) presents a set of examples from the Child Language Data Exchange System (CHILDES) as prototypes of bad transcription practice. Her discussion is based upon four basic confusions. First, Edwards confuses old and discarded versions of CHAT with current CHAT. Second, she confuses the relation between CHAT standards with the implementation of these standards during the process of reformatting older corpora. Third, she confuses transcription for automatic analysis with transcription for documentation. Fourth, she confuses the CHAT guidelines with the larger CHILDES system. We argue that these confusions have misled Edwards into developing an overly rigid set of principles for data analysis which, if followed literally, could choke off progress in the analysis of spontaneous language samples.

Neural Network for Automatic Analysis of Motility Data

1994 ◽  
Vol 33 (01) ◽  
pp. 157-160 ◽  
Author(s):  
S. Kruse-Andersen ◽  
J. Kolberg ◽  
E. Jakobsen
Keyword(s):  
Neural Network ◽  
Muscular Activity ◽  
Recording System ◽  
Automatic Analysis ◽  
Biologically Relevant ◽  
System A ◽  
The Neural Network ◽  
Valuable Method ◽  
Motor Abnormalities ◽  
Trained Network

Abstract:Continuous recording of intraluminal pressures for extended periods of time is currently regarded as a valuable method for detection of esophageal motor abnormalities. A subsequent automatic analysis of the resulting motility data relies on strict mathematical criteria for recognition of pressure events. Due to great variation in events, this method often fails to detect biologically relevant pressure variations. We have tried to develop a new concept for recognition of pressure events based on a neural network. Pressures were recorded for over 23 hours in 29 normal volunteers by means of a portable data recording system. A number of pressure events and non-events were selected from 9 recordings and used for training the network. The performance of the trained network was then verified on recordings from the remaining 20 volunteers. The accuracy and sensitivity of the two systems were comparable. However, the neural network recognized pressure peaks clearly generated by muscular activity that had escaped detection by the conventional program. In conclusion, we believe that neu-rocomputing has potential advantages for automatic analysis of gastrointestinal motility data.

An automatic analysis system for online hotel reviews

2014 ◽  
Author(s):  
Phichayasini Kitwatthanathawon ◽  
Thara Angskun ◽  
Jitimon Angskun
Keyword(s):  
Automatic Analysis ◽  
Analysis System

Application of Computer Vision in The Automatic Analysis of Feeding Behavior inC. elegans

2013 ◽  
Vol 40 (2) ◽  
pp. 188
Author(s):  
Hai-Ning ZHANG ◽  
Wen-Ming HUANG ◽  
Jia-Jun FU ◽  
Xiang-Ping XU ◽  
Tao XU
Keyword(s):  
Computer Vision ◽  
Feeding Behavior ◽  
Automatic Analysis

Algorithms and Tools for the Automatic Analysis of Embedded Systems.

1997 ◽  
Author(s):  
T. A. Henzinger
Keyword(s):  
Embedded Systems ◽  
Automatic Analysis

Automatic Analysis of Emotional Prosody in Mandarin Chinese: Applying the Momel Algorithm

2014 ◽  
Author(s):  
Ting Wang ◽  
Hongwei Ding ◽  
Qiuwu Ma ◽  
Daniel Hirst
Keyword(s):  
Mandarin Chinese ◽  
Automatic Analysis ◽  
Emotional Prosody

Study of a New Benzodiazepine using Automatic Analysis of Sleep Records

2015 ◽  
pp. 491a-494
Author(s):  
J. M. Gaillard ◽  
P. Schultz ◽  
R. Tissot
Keyword(s):  
Automatic Analysis
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