Evaluation of two algorithms for detecting human frequency-following responses to voice pitch.
OBJECTIVE
Voice pitch carries important cues for speech perception in humans. Recent studies have shown the feasibility of recording the frequency-following response (FFR) to voice pitch in normal-hearing listeners. The presence of such a response, however, has been dependent on subjective interpretation of experimenters. The purpose of this study was to develop and test an automated procedure including a control-experimental protocol and response-threshold criteria suitable for extracting FFRs to voice pitch, and compare the results to human judgments.


METHODS
A set of four Mandarin tones (Tone 1 flat; Tone 2 rising; Tone 3 dipping; and Tone 4 falling) were prepared to reflect the four contrastive pitch contours. Two distinctive algorithms, short-term autocorrelation in the time domain and narrow-band spectrogram in the frequency domain, were used to estimate the Frequency Error, Slope Error, Tracking Accuracy, Pitch Strength and Pitch-Noise Ratio of the recordings from individual listeners as well as the power and false-positive rates of each algorithm.


METHODS
Eleven native speakers (five males; age: mean ± SD = 31.4 ± 4.7 years) of Mandarin Chinese were recruited.


RESULTS
The results demonstrated that both algorithms were suitable for extracting FFRs and the objective measures showed comparable results to human judgments.


CONCLUSIONS
The automated procedure used in this study, including the use of the control-experimental protocol and response thresholds used for each of the five objective indices, can be used for difficult-to-test patients and may prove to be useful as an assessment and diagnostic method in both clinical and basic research efforts.
School of Rehabilitation and Communication Sciences, Ohio University, Athens, OH 45701, USA. jeng@ohio.edu
Fuh-Cherng
FC
Jeng
Jiong
J
Hu
Brenda
B
Dickman
Ching-Yu
CY
Lin
Chia-Der
CD
Lin
Ching-Yuan
CY
Wang
Hsiung-Kwang
HK
Chung
Ximing
X
Li
D000161:Acoustic Stimulation; D000328:Adult; D000465:Algorithms; D001302:Audiometry, Speech; D001309:Auditory Threshold; D003463:Cues; D016057:Evoked Potentials, Auditory, Brain Stem; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D010700:Phonetics; D010898:Pitch Perception; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013061:Speech Acoustics; D013067:Speech Perception; D013997:Time Factors; D014831:Voice