scholarly journals Learning to Count Words in Fluent Speech Enables Online Speech Recognition

2021 ◽  
Author(s):  
George Sterpu ◽  
Christian Saam ◽  
Naomi Harte
Keyword(s):  
Speech Recognition ◽  
Fluent Speech

scholarly journals Artificial Neural Networks Combined with the Principal Component Analysis for Non-Fluent Speech Recognition

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 321
Author(s):  
Izabela Świetlicka ◽  
Wiesława Kuniszyk-Jóźkowiak ◽  
Michał Świetlicki
Keyword(s):  
Principal Component Analysis ◽  
Speech Recognition ◽  
Principal Component ◽  
Component Analysis ◽  
Fluent Speech ◽  
Recognition Process ◽  
Observation Matrix ◽  
Analysis Application ◽  
Multilayer Perceptron Network ◽  
Network Application

The presented paper introduces principal component analysis application for dimensionality reduction of variables describing speech signal and applicability of obtained results for the disturbed and fluent speech recognition process. A set of fluent speech signals and three speech disturbances—blocks before words starting with plosives, syllable repetitions, and sound-initial prolongations—was transformed using principal component analysis. The result was a model containing four principal components describing analysed utterances. Distances between standardised original variables and elements of the observation matrix in a new system of coordinates were calculated and then applied in the recognition process. As a classifying algorithm, the multilayer perceptron network was used. Achieved results were compared with outcomes from previous experiments where speech samples were parameterised with the Kohonen network application. The classifying network achieved overall accuracy at 76% (from 50% to 91%, depending on the dysfluency type).

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.

Hesitating About Fluent Speech

1981 ◽  
Vol 26 (2) ◽  
pp. 109-110
Author(s):  
Anthony E. Ades
Keyword(s):  
Fluent Speech

Using an Avatar, RFID & speech recognition for hands-free data collection

2008 ◽  
Author(s):  
Kristie Nemeth ◽  
Nicole Arbuckle ◽  
Andrea Snead ◽  
Drew Bowers ◽  
Christopher Burneka ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Data Collection ◽  
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