Cognitive Audio Interfaces: Mediating Sonic Information With an Understanding of How We Hear

2021 ◽  
pp. 1-10
Author(s):  
Ishwarya Ananthabhotla ◽  
David B. Ramsay ◽  
Clement Duhart ◽  
Joseph A. Paradiso
Keyword(s):  
Author(s):  
Owen Noel Newton Fernando ◽  
Michael Cohen ◽  
Adrian David Cheok

Author(s):  
Craig Nicol ◽  
Stephen Brewster ◽  
Philip Gray
Keyword(s):  

Author(s):  
Marc Emerit ◽  
Pascal Scalart ◽  
André Gilloire

2020 ◽  
Vol 63 (8) ◽  
pp. 2522-2534 ◽  
Author(s):  
Kwang S. Kim ◽  
Hantao Wang ◽  
Ludo Max

Purpose Various aspects of speech production related to auditory–motor integration and learning have been examined through auditory feedback perturbation paradigms in which participants' acoustic speech output is experimentally altered and played back via earphones/headphones “in real time.” Scientific rigor requires high precision in determining and reporting the involved hardware and software latencies. Many reports in the literature, however, are not consistent with the minimum achievable latency for a given experimental setup. Here, we focus specifically on this methodological issue associated with implementing real-time auditory feedback perturbations, and we offer concrete suggestions for increased reproducibility in this particular line of work. Method Hardware and software latencies as well as total feedback loop latency were measured for formant perturbation studies with the Audapter software. Measurements were conducted for various audio interfaces, desktop and laptop computers, and audio drivers. An approach for lowering Audapter's software latency through nondefault parameter specification was also tested. Results Oft-overlooked hardware-specific latencies were not negligible for some of the tested audio interfaces (adding up to 15 ms). Total feedback loop latencies (including both hardware and software latency) were also generally larger than claimed in the literature. Nondefault parameter values can improve Audapter's own processing latency without negative impact on formant tracking. Conclusions Audio interface selection and software parameter optimization substantially affect total feedback loop latency. Thus, the actual total latency (hardware plus software) needs to be correctly measured and described in all published reports. Future speech research with “real-time” auditory feedback perturbations should increase scientific rigor by minimizing this latency.


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