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. Design. 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. Study Sample. 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. © 2011 British Society of Audiology, International Society of Audiology, and Nordic Audiological Society.
International Journal of Audiology
Jeng, Fuh Cherng; Hu, Jiong; Dickman, Brenda; Lin, Ching Yu; Lin, Chia Der; Wang, Ching Yuan; Chung, Hsiung Kwang; and Li, Ximing, "Evaluation of two algorithms for detecting human frequency-following responses to voice pitch" (2010). All Faculty Scholarship. 72.