Parametric and non-parametric signal analysis for mapping air flow in the ear-canal to tongue movements: a new strategy for hands-free human-machine interfaces

2006 IEEE 12th Digital Signal Processing Workshop &Amp;amp; 4th IEEE Signal Processing Education Workshop

2006

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Speech collected through a microphone placed in front of the mouth has been the primary source of data collection for speech recognition. However, this set-up also picks up any ambient noise present at the same time. As a result, locations which may provide shielding from surrounding noise have also been considered. This study considers an ear-insert microphone which collects speech from the ear canal to take advantage of the ear canal noise shielding properties to operate in noisy environments. Speech segmentation is achieved using short-time signal magnitude and short-time energy-entropy features. Cepstral coefficients extracted from each segmented utterance are used as input features to a back-propagation neural network for the seven isolated word recognizer implemented. Results show that a backpropagation neural network configuration may be a viable choice for this recognition task and that the best average recognition rate (94.73%) is obtained with melfrequency cepstral coefficients for a two-layer network.Index Terms -speech processing, in-ear microphone, backpropagation neural network

Section: Introductionmentioning

confidence: 90%

In-Ear Microphone Speech Data Segmentation and Recognition using Neural Networks

Bulbuller

Fargues²,

2006 IEEE 12th Digital Signal Processing Workshop &Amp;amp; 4th IEEE Signal Processing Education Workshop

2006

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“…The system makes use of changes in air pressure or sound waves (vibrations) in the ear to characterize measured parameters. Research has shown that initiating actions, in particular movements of the tongue [3,4] and speech, produce detectable pressure waves with strength corresponding to the direction, speed and/or intensity of the action*..…”

Section: Machine Interface Systemmentioning

confidence: 99%

“…In this work, we introduce a method for detecting both tongue movement and speech, and generating a control instruction corresponding to that action that can be applied to any teleoperated or semi-autonomous robot. We have previously reported on the development of a non-intrusive tonguemovement based machine interface without the need for insertion of any device within the oral cavity [3,4]. This interface consists of tracking tongue movement by monitoring changes in airflow that occur in the ear canal.…”

Section: Introductionmentioning

confidence: 99%

A Dual-Mode Human-Machine Interface for Robotic Control based on Acoustic Sensitivity of the Aural Cavity

The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006.

Fargues

Gupta³

et al.

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.Abstract -We introduce an unobtrusive sensor-based control system for human-machine interface to control robotic and rehabilitative devices. The interface is capable of directing robotic or assist devices in response to tongue movement and/or speech without insertion of any device in the vicinity of the oral cavity. The interface is centered on the unique properties of the human ear as an acoustic output device.Our work has shown that various movements within the oral cavity create unique, traceable pressure changes in the human ear, which can be measured with a simple sensor (such as a microphone) and analysed to produce commands signals, which can in turn be used to control robotic devices.In this work, we present: 1) an analysis of the sensitivity of human ear canals as acoustic output device, 2) the design of a new sensor for monitoring airflow in the aural canal, 3) pattern recognition procedures for recognition of both speech and tongue movement by monitoring aural flow across several human test subjects, and 4) a conceptual design and simulation of the machine interface system.

“…We have explored, matched filtering, autoregressive modeling, and non-linear alignment methods to determine the signal classes [5]. Non-linear alignment has shown the greatest promise for recognition accuracy, and is thus enumerated for telerobotic applications.…”

Section: B Signal Recognition and Classificationmentioning

confidence: 99%

“…For example, if a "right" tongue movement was performed, a 97.98% probability of the robot receiving this signal was assumed, with a 2.02% probability of the robot receiving a "top" (forward movement) signal instead. Our work [5] has shown an 0.2 second interval typifies nearly all recorded tongue movements, thus this delay was assumed between movement commands. Figure 8 shows the results of a simple simulation where the interface was implemented to direct the robot to reach a series of (20) waypoints in a planar work space.…”

Section: Robotic Performance Simulationmentioning

confidence: 99%

Human-machine interface for tele-robotic operation: mapping of tongue movements based on aural flow monitoring

2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)

Gupta²,

Chung³

et al.

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Abstract-A new human-machine interface is introduced for "hands-free" tele-operation of mobile robots. This interface consists of tracking tongue movement by monitoring changes in airflow that occur in the ear canal. Tongue movements within the human oral cavity create unique, subtle pressure signals in the ear that can be processed to produce commands signals in response to that movement. Once recognized, said movements can in turn be used in for robotic tele-operation. The complete strategy is tested on 4 tongue actions: touching the tongue to the left and right corners of the mouth, and to the top and bottom center of the mouth. Through extensive experiments, it is shown that the pressure signals due to tongue movements are distinct and can be detected with over 97% accuracy. A case study to control the Whegs II robotic platform has specifically been investigated. Based on simulation results, it is concluded that this unique strategy will make hands-free robotic tele-operation a practical reality.