A theoretical analysis of speech recognition based on feature trajectory models

2004 ◽  
Author(s):  
Yasuhiro Minami ◽  
Erik McDermott ◽  
Atsushi Nakamura ◽  
Shigeru Katagiri
Keyword(s):  
Speech Recognition ◽  
Theoretical Analysis ◽  
Trajectory Models ◽  
Feature Trajectory

Hybrid neural predictor/stochastic trajectory models for Chinese speech recognition

1999 ◽  
Vol 35 (10) ◽  
pp. 818 ◽  
Author(s):  
Xinye Huang ◽  
Xiaohui Ma ◽  
Yuqing Fu ◽  
Jiren Lu
Keyword(s):  
Speech Recognition ◽  
Trajectory Models

Theoretical Analysis of Diversity in an Ensemble of Automatic Speech Recognition Systems

2014 ◽  
Vol 22 (3) ◽  
pp. 711-726 ◽  
Author(s):  
Kartik Audhkhasi ◽  
Andreas M. Zavou ◽  
Panayiotis G. Georgiou ◽  
Shrikanth S. Narayanan
Keyword(s):  
Speech Recognition ◽  
Theoretical Analysis ◽  
Automatic Speech Recognition ◽  
Recognition Systems

Microdiffraction Patterns of Small Metallic Particles II; Theoretical Analysis

1982 ◽  
Vol 40 ◽  
pp. 668-669
Author(s):  
A. Gómez ◽  
P. Schabes-Retchkiman ◽  
M. José-Yacamán ◽  
T. Ocaña
Keyword(s):  
Experimental Data ◽  
Electron Diffraction ◽  
Theoretical Analysis ◽  
Size Range ◽  
Dynamical Theory ◽  
Metallic Particles ◽  
Splitting Effect

The splitting effect that is observed in microdiffraction pat-terns of small metallic particles in the size range 50-500 Å can be understood using the dynamical theory of electron diffraction for the case of a crystal containing a finite wedge. For the experimental data we refer to part I of this work in these proceedings.

Selecting the Optimal FM System for Children With Cochlear Implants

2008 ◽  
Vol 18 (1) ◽  
pp. 19-24
Author(s):  
Erin C. Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Empirical Research ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Evidence Based ◽  
Signal To Noise ◽  
Speech Processor ◽  
System Input ◽  
Optimal Type

Children who use cochlear implants experience significant difficulty hearing speech in the presence of background noise, such as in the classroom. To address these difficulties, audiologists often recommend frequency-modulated (FM) systems for children with cochlear implants. The purpose of this article is to examine current empirical research in the area of FM systems and cochlear implants. Discussion topics will include selecting the optimal type of FM receiver, benefits of binaural FM-system input, importance of DAI receiver-gain settings, and effects of speech-processor programming on speech recognition. FM systems significantly improve the signal-to-noise ratio at the child's ear through the use of three types of FM receivers: mounted speakers, desktop speakers, or direct-audio input (DAI). This discussion will aid audiologists in making evidence-based recommendations for children using cochlear implants and FM systems.

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