scholarly journals ERP correlates of pitch error detection in complex Tone and Voice auditory feedback with missing fundamental

2012 ◽  
Vol 1448 ◽  
pp. 89-100 ◽  
Author(s):  
Roozbeh Behroozmand ◽  
Oleg Korzyukov ◽  
Charles R. Larson
Keyword(s):  
Error Detection ◽  
Auditory Feedback ◽  
Complex Tone ◽  
Pitch Error ◽  
Missing Fundamental

Visual and auditory feedback to improve touchscreen usability in turbulence

2017 ◽  
Vol 61 (1) ◽  
pp. 89-93
Author(s):  
Yuzhi Wan ◽  
Julie C. Prinet ◽  
Nadine Sarter
Keyword(s):  
Error Detection ◽  
Auditory Feedback ◽  
Completion Time ◽  
Text Entry ◽  
Mobile Environments ◽  
Military Aircraft ◽  
Flight Decks ◽  
Performance Effects ◽  
Flight Deck ◽  
Completion Times

Touchscreens are being introduced to various mobile environments that are, at times, affected by vibrations and turbulence, such as modern car cockpits or flight decks of commercial and military aircraft. To assess and enhance the usability of touchscreens in these domains, this experiment examined the performance effects of turbulence on two flight-related tasks and the effectiveness of visual and auditory feedback for supporting error detection, fast completion times and multitasking. Nineteen pilots performed a flight plan entry and a checklist task in calm and turbulent conditions during manual flight and on autopilot. Results show that unaided performance suffers greatly in turbulence, both in terms of the number of errors and completion time. However, visual and auditory feedback both helped reduce these performance costs by improving error detection and multitasking. Participants preferred auditory feedback for text entry during manual flight and in turbulence. The findings from this study can inform the design and evaluation of touch screens for mobile environments, such as the flight deck, ambulances and surveillance operations.

scholarly journals Dynamics of Self-monitoring and Error Detection in Speech Production: Evidence from Mental Imagery and MEG

2015 ◽  
Vol 27 (2) ◽  
pp. 352-364 ◽  
Author(s):  
Xing Tian ◽  
David Poeppel
Keyword(s):  
Speech Production ◽  
Mental Imagery ◽  
Error Detection ◽  
Auditory Feedback ◽  
Spectral Difference ◽  
Self Monitoring ◽  
Onset Delay ◽  
Nonmonotonic Function ◽  
Four Levels ◽  
Pitch Shift

A critical subroutine of self-monitoring during speech production is to detect any deviance between expected and actual auditory feedback. Here we investigated the associated neural dynamics using MEG recording in mental-imagery-of-speech paradigms. Participants covertly articulated the vowel /a/; their own (individually recorded) speech was played back, with parametric manipulation using four levels of pitch shift, crossed with four levels of onset delay. A nonmonotonic function was observed in early auditory responses when the onset delay was shorter than 100 msec: Suppression was observed for normal playback, but enhancement for pitch-shifted playback; however, the magnitude of enhancement decreased at the largest level of pitch shift that was out of pitch range for normal conversion, as suggested in two behavioral experiments. No difference was observed among different types of playback when the onset delay was longer than 100 msec. These results suggest that the prediction suppresses the response to normal feedback, which mediates source monitoring. When auditory feedback does not match the prediction, an “error term” is generated, which underlies deviance detection. We argue that, based on the observed nonmonotonic function, a frequency window (addressing spectral difference) and a time window (constraining temporal difference) jointly regulate the comparison between prediction and feedback in speech.

Impairment of Speech Auditory Feedback Error Detection and Motor Correction in Post-Stroke Aphasia

2021 ◽  
pp. 106163
Author(s):  
Stacey Sangtian ◽  
Yuan Wang ◽  
Julius Fridriksson ◽  
Roozbeh Behroozmand
Keyword(s):  
Error Detection ◽  
Auditory Feedback ◽  
Post Stroke ◽  
Feedback Error

scholarly journals A dynamic machine tool circle test calibration method by R-test

2018 ◽  
Vol 249 ◽  
pp. 02004
Author(s):  
dehou Qian ◽  
qingzhen Bi
Keyword(s):  
Machine Tool ◽  
Error Detection ◽  
Manufacturing Industry ◽  
Production Efficiency ◽  
Dynamic Test ◽  
Calibration Method ◽  
Initial Position ◽  
Test Method ◽  
Error Sources ◽  
Pitch Error

With the continuous popularization of automation in the manufacturing industry and continuous improvement of production efficiency, new requirements have been put forward for the error detection of machine tool. As a new automated detection tool, R-test has been widely studied by scholars. This paper proposes a dynamic test method for R-test, and analyses the influence of three main error sources of servo error, pitch error and reading error. The corresponding elimination methods are also introduced. An experiment on a double turntable machine tool was conducted to verify the analysis. In addition, the selection of feed rate and initial position in circle test is also studied.

scholarly journals Time-dependent Neural Processing of Auditory Feedback during Voice Pitch Error Detection

2011 ◽  
Vol 23 (5) ◽  
pp. 1205-1217 ◽  
Author(s):  
Roozbeh Behroozmand ◽  
Hanjun Liu ◽  
Charles R. Larson
Keyword(s):  
Error Detection ◽  
Auditory Feedback ◽  
Stimulus Presentation ◽  
Time Dependent ◽  
Neural Processing ◽  
Monitoring And Control ◽  
Neural Responses ◽  
Feedback Processing ◽  
Passive Listening ◽  
Error Detection And Correction

The neural responses to sensory consequences of a self-produced motor act are suppressed compared with those in response to a similar but externally generated stimulus. Previous studies in the somatosensory and auditory systems have shown that the motor-induced suppression of the sensory mechanisms is sensitive to delays between the motor act and the onset of the stimulus. The present study investigated time-dependent neural processing of auditory feedback in response to self-produced vocalizations. ERPs were recorded in response to normal and pitch-shifted voice auditory feedback during active vocalization and passive listening to the playback of the same vocalizations. The pitch-shifted stimulus was delivered to the subjects' auditory feedback after a randomly chosen time delay between the vocal onset and the stimulus presentation. Results showed that the neural responses to delayed feedback perturbations were significantly larger than those in response to the pitch-shifted stimulus occurring at vocal onset. Active vocalization was shown to enhance neural responsiveness to feedback alterations only for nonzero delays compared with passive listening to the playback. These findings indicated that the neural mechanisms of auditory feedback processing are sensitive to timing between the vocal motor commands and the incoming auditory feedback. Time-dependent neural processing of auditory feedback may be an important feature of the audio-vocal integration system that helps to improve the feedback-based monitoring and control of voice structure through vocal error detection and correction.

Error Monitoring in People Who Stutter

1992 ◽  
Vol 35 (5) ◽  
pp. 1024-1032 ◽  
Author(s):  
Albert Postma ◽  
Herman Kolk
Keyword(s):  
False Alarm ◽  
White Noise ◽  
Speech Production ◽  
Error Detection ◽  
Auditory Feedback ◽  
The Self ◽  
Tape Recording ◽  
Detection Accuracy ◽  
Error Monitoring ◽  
Self Monitoring

Several theories purport that people who stutter suffer a speech-auditory feedback defect. The disordered feedback creates the illusion that some kind of error has intruded into the speech flow. Stuttering then results from actions aimed to correct the suspected, but nonexistent, error. These auditory feedback defect theories thus predict deviant error detection performance in people who stutter during speech production. To test this prediction, subjects who stuttered and those who did not had to detect self-produced (phonemic) speech errors while speaking with normal auditory feedback and with the auditory feedback masked by white noise. The two groups did not differ significantly in error detection accuracy and speed, nor in false alarm scores. This opposes auditory feedback defect theories and suggests that the self-monitoring processes of people who stutter function normally. In a condition in which errors had to be detected in other-produced speech, i.e., while listening to a tape recording, subjects who stuttered did detect fewer errors. Whether this might signal some general phonological problem is discussed.

scholarly journals Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch

2014 ◽  
Vol 84 (1) ◽  
pp. 97-108 ◽  
Author(s):  
Roozbeh Behroozmand ◽  
Nadine Ibrahim ◽  
Oleg Korzyukov ◽  
Donald A. Robin ◽  
Charles R. Larson
Keyword(s):  
Left Hemisphere ◽  
Error Detection ◽  
Absolute Pitch ◽  
Pitch Error ◽  
Vocal Pitch

Melody, not Beat Perception, Predicts Rhythmic Error Detection

2021 ◽  
pp. 002242942110321
Author(s):  
Bryan E. Nichols ◽  
Laura A. Stambaugh
Keyword(s):  
Regression Model ◽  
Error Detection ◽  
Future Research ◽  
Musical Experience ◽  
Rhythm Perception ◽  
Pitch Error ◽  
Tempo Change ◽  
Two Measures

The purpose of this study was to examine the relationships among beat perception, error detection, and musical experience. We presented monophonic rhythms using a piano timbre along with two measures of beat perception (Harvard Beat Finding and Interval Test [BFIT] and Goldsmiths Beat Alignment Test) and a measure of melodic error detection. College musicians’ ( N = 43) ability to detect rhythm errors was not significantly correlated to their ability to perceive beat alignment (Goldsmiths test) or tempo change (BFIT). Age was related to performance on only one of the measures, the BFIT test. A regression model yielded pitch error detection as the only significant predictor of rhythmic error detection. We suggest that college musicians already possess a requisite ability for beat processing that allows them to perform error detection. The lack of relationship between beat perception and rhythmic error detection is explained by this requisite ability in the population, and we promote future research for pitch and rhythm processing as it relates to rhythm perception or performance.

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