The time course of auditory recognition measured with rapid sequences of short natural sounds

Abstract

Human listeners are able to recognize accurately an impressive range of complex sounds, such as musical instruments or voices. The underlying mechanisms are still poorly understood. Here, we aimed to characterize the processing time needed to recognize a natural sound. To do so, by analogy with the “rapid visual sequential presentation paradigm”, we embedded short target sounds within rapid sequences of distractor sounds. The core hypothesis is that any correct report of the target implies that sufficient processing for recognition had been completed before the time of occurrence of the subsequent distractor sound. We conducted four behavioral experiments using short natural sounds (voices and instruments) as targets or distractors. We report the effects on performance, as measured by the fastest presentation rate for recognition, of sound duration, number of sounds in a sequence, the relative pitch between target and distractors and target position in the sequence. Results showed a very rapid auditory recognition of natural sounds in all cases. Targets could be recognized at rates up to 30 sounds per second. In addition, the best performance was observed for voices in sequences of instruments. These results give new insights about the remarkable efficiency of timbre processing in humans, using an original behavioral paradigm to provide strong constraints on future neural models of sound recognition.

Listening in the Mix: Lead Vocals Robustly Attract Auditory Attention in Popular Music

“…These findings support a unique role of the lead vocals in musical scene perception. More generally, this pattern of results is consistent with previous work in which singing voices have been shown to be perceptually privileged compared to other musical instruments by yielding faster processing ( Agus et al, 2012 ) and more precise recognition rates (e.g., Suied et al, 2014 ; Isnard et al, 2019 ) as well as a stronger cortical representation (e.g., Levy et al, 2001 ) compared to other instruments. Our results demonstrate that auditory attention is drawn to the lead vocals in a mix, which complements knowledge about pre-attentive perceptual biases in musical scene analysis such as the high-voices superiority effect ( Trainor et al, 2014 ).…”

“…We will refer to this unique characteristic as “lead vocal salience” in the following. This finding is in line with the unique role of singing voices documented in previous experiments, where voices were processed faster and more accurately in comparison to other musical instruments (e.g., Agus et al, 2012 ; Suied et al, 2014 ; Isnard et al, 2019 ) and were shown to have a unique cortical voice-specific-response indicating a specialized processing for human voices (e.g., Levy et al, 2001 ).…”

“…In Western popular music, the lead melody and thus the centerpiece of a song is sung by a human voice (lead vocals), which is accompanied by a variety of instruments and, at times, background vocals. Recent studies have shown that the voice occupies a unique role among other sound sources (e.g., Belin et al, 2000 ; Levy et al, 2001 ; Agus et al, 2012 ; Suied et al, 2014 ; Isnard et al, 2019 ). In a neurophysiological study, Belin et al (2000) examined the response to speech, vocal non-speech sounds, and non-vocal environmental sounds.…”

“…Accuracy for voices was higher and reaction times were faster than for all other target categories, indicating an advantage in processing voices. Studies by Suied et al (2014) and Isnard et al (2019) focused on the recognition of timbre in short glimpses of recorded sounds that differed only in timbre. Again, singing voices stood out by achieving recognition above chance level with a sound duration of only 4 ms, while all other instrument categories required 8 ms durations.…”

Human voices escape the auditory attentional blink: Evidence from detections and pupil responses

“…By measuring RTs during this task, they observed faster responses for human voice targets compared to targets belonging to percussion and string instruments, and for voice-instrument chimeras 3 among musical instrument and instrumental chimera distracters. More recently, Isnard et al (2019) used the fastest presentation rate that allows for accurate recognition as a measure of processing time. In this behavioural study, voices could still be recognized among instrumental sound distracters at a very rapid rate (i.e., 30 Hz), and the fastest processing times were obtained for human voices.…”