Literature DB >> 21498575

Accuracy of the NDI wave speech research system.

Jeffrey J Berry1.   

Abstract

PURPOSE: This work provides a quantitative assessment of the positional tracking accuracy of the NDI Wave Speech Research System.
METHOD: Three experiments were completed: (a) static rigid-body tracking across different locations in the electromagnetic field volume, (b) dynamic rigid-body tracking across different locations within the electromagnetic field volume, and (c) human jaw-movement tracking during speech. Rigid-body experiments were completed for 4 different instrumentation settings, permuting 2 electromagnetic field volume sizes with and without automated reference sensor processing.
RESULTS: Within the anthropometrically pertinent "near field" (< 200 mm) of the NDI Wave field generator, at the 300-mm(3) volume setting, 88% of dynamic positional errors were < 0.5 mm and 98% were < 1.0 mm. Extreme tracking errors (> 2 mm) occurred within the near field for < 1% of position samples. For human jaw-movement tracking, 95% of position samples had < 0.5 mm errors for 9 out of 10 subjects.
CONCLUSIONS: Static tracking accuracy is modestly superior to dynamic tracking accuracy. Dynamic tracking accuracy is best for the 300-mm(3) field setting in the 200-mm near field. The use of automated head correction has no deleterious effect on tracking. Tracking errors for jaw movements during speech are typically < 0.5 mm.

Entities:  

Mesh:

Year:  2011        PMID: 21498575     DOI: 10.1044/1092-4388(2011/10-0226)

Source DB:  PubMed          Journal:  J Speech Lang Hear Res        ISSN: 1092-4388            Impact factor:   2.297


  22 in total

1.  An Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification.

Authors:  Jun Wang; Ashok Samal; Panying Rong; Jordan R Green
Journal:  J Speech Lang Hear Res       Date:  2016-02       Impact factor: 2.297

2.  Accuracy and precision of a custom camera-based system for 2-d and 3-d motion tracking during speech and nonspeech motor tasks.

Authors:  Yongqiang Feng; Ludo Max
Journal:  J Speech Lang Hear Res       Date:  2014-04-01       Impact factor: 2.297

3.  Automatic prediction of intelligible speaking rate for individuals with ALS from speech acoustic and articulatory samples.

Authors:  Jun Wang; Prasanna V Kothalkar; Myungjong Kim; Andrea Bandini; Beiming Cao; Yana Yunusova; Thomas F Campbell; Daragh Heitzman; Jordan R Green
Journal:  Int J Speech Lang Pathol       Date:  2018-11-08       Impact factor: 2.484

4.  Simultaneous electromagnetic articulography and electroglottography data acquisition of natural speech.

Authors:  Sarah Harper; Sungbok Lee; Louis Goldstein; Dani Byrd
Journal:  J Acoust Soc Am       Date:  2018-11       Impact factor: 1.840

5.  Recognizing Whispered Speech Produced by an Individual with Surgically Reconstructed Larynx Using Articulatory Movement Data.

Authors:  Beiming Cao; Myungjong Kim; Ted Mau; Jun Wang
Journal:  Workshop Speech Lang Process Assist Technol       Date:  2016-09

6.  Predicting Intelligible Speaking Rate in Individuals with Amyotrophic Lateral Sclerosis from a Small Number of Speech Acoustic and Articulatory Samples.

Authors:  Jun Wang; Prasanna V Kothalkar; Myungjong Kim; Yana Yunusova; Thomas F Campbell; Daragh Heitzman; Jordan R Green
Journal:  Workshop Speech Lang Process Assist Technol       Date:  2016-09

7.  Indexing head movement during speech production using optical markers.

Authors:  Kevin D Roon; Katherine M Dawson; Mark K Tiede; D H Whalen
Journal:  J Acoust Soc Am       Date:  2016-05       Impact factor: 1.840

8.  Multimodal Speech Capture System for Speech Rehabilitation and Learning.

Authors:  Nordine Sebkhi; Dhyey Desai; Mohammad Islam; Jun Lu; Kimberly Wilson; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Eng       Date:  2017-01-18       Impact factor: 4.538

9.  Speaker-Independent Silent Speech Recognition from Flesh-Point Articulatory Movements Using an LSTM Neural Network.

Authors:  Myungjong Kim; Beiming Cao; Ted Mau; Jun Wang
Journal:  IEEE/ACM Trans Audio Speech Lang Process       Date:  2017-11-23

10.  Encoding of Articulatory Kinematic Trajectories in Human Speech Sensorimotor Cortex.

Authors:  Josh Chartier; Gopala K Anumanchipalli; Keith Johnson; Edward F Chang
Journal:  Neuron       Date:  2018-05-17       Impact factor: 17.173

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.