“Auditory learning” papers

An interesting phenomenon in science is how the discovery of new techniques, findings, or theoretical understanding can produce cyclical waves of interest in a research area. Such is the case for perceptual learning, which is currently enjoying a renaissance following previous periods of excitement, some 50 and 100 years ago In this issue, Karmarkar and

Cited by 20Open access

Going beyond rote auditory learning: Neural patterns of generalized auditory learning

Shannon L. M. Heald, Stephen C. Van Hedger, John P. Veillette et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2021

Abstract The ability to generalize rapidly across specific experiences is vital for robust recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. Behavioral research has demonstrated that listeners are rapidly able to generalize their experience with a talker’s speech and quickly improve understanding of a difficult-to-understand talker without prolonged practice, e.g., even after a single training session. Here, we examine the differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker using a Pretest-Posttest design with electroencephalography (EEG). Participants were trained using either (1) a large inventory of words where no words repeated across the experiment (generalized learning) or (2) a small inventory of words where words repeated (rote learning). Analysis of long-latency auditory evoked potentials at Pretest and Posttest revealed that while rote and generalized learning both produce rapid changes in auditory processing, the nature of these changes differed. In the context of adapting to a talker, generalized learning is marked by an amplitude reduction in the N1-P2 complex and by the presence of a late-negative (LN) wave in the auditory evoked potential following training. Rote learning, however, is marked only by temporally later source configuration changes. The early N1-P2 change, found only for generalized learning, suggests that generalized learning relies on the attentional system to reorganize the way acoustic features are selectively processed. This change in relatively early sensory processing (i.e. during the first 250ms) is consistent with an active processing account of speech perception, which proposes that the ability to rapidly adjust to the specific vocal characteristics of a new talker (for which rote learning is rare) relies on attentional mechanisms to adaptively tune early auditory processing sensitivity. Statement of Significance Previous research on perceptual learning has typically examined neural responses during rote learning: training and testing is carried out with the same stimuli. As a result, it is not clear that findings from these studies can explain learning that generalizes to novel patterns, which is critical in speech perception. Are neural responses to generalized learning in auditory processing different from neural responses to rote learning? Results indicate rote learning of a particular talker’s speech involves brain regions focused on the memory encoding and retrieving of specific learned patterns, whereas generalized learning involves brain regions involved in reorganizing attention during early sensory processing. In learning speech from a novel talker, only generalized learning is marked by changes in the N1-P2 complex (reflective of secondary auditory cortical processing). The results are consistent with the view that robust speech perception relies on the fast adjustment of attention mechanisms to adaptively tune auditory sensitivity to cope with acoustic variability.

Cited by 0Open access

LEARNING STYLES: Visual, auditory

Created Spice, Judit Ungvari-martin, Nate Stewart et al. · 2010

Cited by 0

Auditory registration without learning.

Sonya M. Sheffert, Richard M. Shiffrin · Journal of Experimental Psychology Learning Memory and Cognition · 2003

In 3 studies, the authors explore how repeated exposure to a spoken word affects memory for perceptual attributes associated with the word (such as a talker's voice or a word's plurality). Subjects heard a list of words; particular words were repeated differing numbers of times. At test, subjects estimated the frequency of each word, with instructions to give frequency judgments of "zero" to words with changed attributes. The experiments demonstrate that memory for perceptual attributes improves very little after the first few repetitions, although word memory continues to improve. The experiments extend the registration without learning effect (D. L. Hintzman, T. Curran, & B. Oppy, 1992) to auditory words, to complex attributes (voice), and to conditions of low and high stimulus variability (two or many voices).

Cited by 11

Incidental auditory category learning.

Gabay, Yafit, Dick, Frederic K., Zevin, Jason D. et al. · KiltHub Repository · 2018

Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in 1 of 4 possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from 1 of 4 distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning.

Cited by 0Open access

Incidental auditory category learning

Lori L. Holt, Yafit Gabay, Frederic Dick et al. · The Journal of the Acoustical Society of America · 2015

Little is known about how auditory categories are learned incidentally—that is, in the absence of overt category decisions or experimenter-provided feedback. This is an important gap, as learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, where participants rapidly detect and report the appearance of a visual target in one of four possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from one of four distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to theories of incidental phonetic category learning.

Cited by 13Open access

Auditory Learning: A Perspective

2024

Cited by 0

Incidental auditory category learning.

Yafit Gabay, Frederic Dick, Jason D. Zevin et al. · Journal of Experimental Psychology Human Perception & Performance · 2015

Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in 1 of 4 possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from 1 of 4 distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning.

Cited by 41Open access

Auditory Affective Verbal Learning

Prof. Dr. Norbert M. Seel · 2012

Cited by 0

Auditory development and learning

Karen Mattock, Sygal Amitay, David R. Moore · Oxford University Press eBooks · 2010

Like all living systems, auditory system function is constantly changing in response to internal and external forces—genetic, disease, and experience. It has long been recognized, for example, that the fundamental measure of hearing, the pure-tone audiogram, is susceptible to both developmental and learning influences. And the deterioration of hearing sensitivity in later life is thought to be influenced by inheritance, acting synergistically with environmental (noise, toxins) and biological (ageing) processes. Research into the long-term dynamics of hearing is, despite much increased effort and under- standing over recent years, still in its infancy. The organization of this chapter mimics the history of research in the field. While we provide an overview of the most significant, older findings, the primary focus of our presentation is on the recent and, we think, exciting findings of the last decade. The bias of our work reflects our backgrounds, in experimental psychology and neuroscience. Those seeking alternative perspectives are directed to appropriate reviews in the overview that follows.

Cited by 7

Auditory Verbal Learning Test

Sara Cavaco, Cláudia Pinto, Alexandra Gonçalves et al. · Psychologica · 2008

O Auditory Verbal Learning Test (AVLT) é uma das provas neuropsicológicas mais usadas em todo o mundo, na prática clínica e de investigação. Após a adaptação da prova à população Portuguesa, foram recolhidos dados normativos numa amostra de 287 sujeitos (entre os 21 e os 65 anos) sem evidência ou história de alterações neurológicas ou psiquiátricas. Com o aumento da idade verificou-se uma pioria na evocação livre e no reconhecimento diferido. O índice de aprendizagem não variou com a idade. A influência das variáveis escolaridade e sexo foi menos consistente.

Cited by 1Open access

Lesson 1.3: Auditory Learning

Phyllis Nissila · 2016

Cited by 0

Search 250 million research papers