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Incidental Auditory Category Training for Language Learning

Examining the Impact of Non-linguistic Incidental Auditory Category Training on Adult Language Acquisition

Status
Terminated
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04509024
Acronym
IACT
Enrollment
106
Registered
2020-08-11
Start date
2019-09-01
Completion date
2023-01-10
Last updated
2024-07-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Healthy, Language

Keywords

Learning, Speech, Cognition

Brief summary

The overarching goal of the proposed research is to understand how human listeners learn speech categories. The project takes a prospective approach with adult second-language learners, blending empirical, methodological and theoretical advances from laboratory studies with explicit classroom instruction. The central hypothesis is that incidentally-acquired nonlinguistic perceptual building block categories may support speech perception and production in a second language. The project will advance important theoretical debates about the cross-talk between general auditory representations and speech categories and will provide a novel approach to nudging adult learners off learning plateau typically encountered in classroom instruction.

Detailed description

Robust speech communication requires that listeners learn linguistically-relevant representations for stable language regularities, such as the speech sounds (phonemes) that convey meaning. In an increasingly multilingual society, as many as twenty percent of Americans accomplish this across multiple languages. Yet, second language acquisition is especially challenging among adult language learners, for whom learning typically involves explicit classroom instruction. Troublingly, research documents that instruction routinely results in a 'learning plateau' whereby language abilities stagnate or even atrophy despite continued instruction. There is a need to establish effective new approaches to nudge adult language learners off this plateau. This project integrates theoretical and methodological developments in auditory category learning with approaches to classroom-based L2 instruction. Specifically, incidental category learning (in which learners' attention is directed away from to-be-learned categories by an engaging videogame) taps into category learning systems distinct from those engaged in more explicit learning. Moreover, incidental learning of nonspeech sound categories leads to activation of putatively speech-selective cortex associated with speech categorization, suggesting potential representational cross-talk. This guides the central hypothesis of the project: incidental learning of nonspeech perceptual building block categories may provide a 'back door' through which to influence adult L2 learners' speech acquisition and to move them off the classroom learning plateau. An intensive 8-week incidental training study will test the hypothesis (Aim 1). Comparison of incidental nonspeech training with explicit L2 speech training will assess whether this cognitive 'back door' may be more effective in promoting L2 speech perception and production than explicit training with L2 speech and will determine the extent to which each interacts with classroom instruction in the L2 (Aim 2). The results will reveal whether nonspeech, auditory categories sharing common perceptual dimensions with second language categories scaffold L2 acquisition, the degree to which explicit instruction may support or interfere with new auditory categories, whether incidental learning is retained after training, and whether learning gains transfer to support other language-learning tasks. In blending empirical, methodological, and theoretical advances from laboratory studies with explicit classroom learning it will be possible to determine the interplay between incidentally-acquired nonlinguistic perceptual building block categories and an emerging L2. This will advance important theoretical debates about the cross-talk between general auditory representations and speech categories and will provide a novel approach to L2 pedagogy.

Interventions

BEHAVIORALIncidental training

Training involving non-speech sounds embedded in a video-game.

BEHAVIORALExplicit training

Training involving explicit sound and category information

Structured adult classroom language training.

BEHAVIORALClassroom and incidental training

Both classroom and incidental training.

BEHAVIORALClassroom and explicit training

Both classroom and explicit training.

Sponsors

Carnegie Mellon University
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* 18 or older, normal hearing * Native/non-native Chinese speakers

Exclusion criteria

* Younger than 18, loss of hearing

Design outcomes

Primary

MeasureTime frameDescription
Change in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of TrainingPre-test (baseline) and immediately after 2 months of training.Each participant's 96 auditory discrimination data points at Pre-test and Post-test, respectively, were reduced to one sensitivity score: d-prime (d': hits minus false alarms). This transformation takes into account response bias and approaches a normal distribution. A higher score represents greater sensitivity. The difference in scores from pre- to post-test represents the change.
Change in Auditory Category Learning Accuracy After 2 Months of TrainingPre-test (baseline) and immediately after 2 months of training.Each participant's 96 auditory categorization data points at Pre-test and Post-test, respectively, were turned into a mean of the correct answers. The difference between the two accuracy scores represents the mean change in accuracy.
Novel Auditory Word Learning Accuracy After 2 Months of TrainingImmediately after 2 months of training.At post-test, participants did a three day novel word learning task. Their 48 word identification data points on the first and third days, respectively, were turned into a mean correct score. The difference in scores from Day 1 to Day 3 represents the change in mean novel word learning accuracy.

Secondary

MeasureTime frameDescription
Word Recognition Accuracy in Unrelated Language 3 Months After Training3 months post-interventionThree months after training, participants were scheduled to learn words in an unrelated language. Their mean accuracy would be calculated.

Countries

United States

Participant flow

Pre-assignment details

This is the number of participants who agreed to participate in the study following completion of the informed consent process.

Participants by arm

ArmCount
Incidental Training
Participants play a video-game involving non-speech.
18
Explicit Training
Participants use a website involving explicit sounds and labels.
17
No Training
Participants do not undergo training between pre- and post-tests.
19
Classroom Training
Participants take part in a weekly structured language class.
17
Classroom and Incidental Training
Participants take part in classroom and video-game training.
18
Classroom and Explicit Training
Participants take part in classroom and explicit web-based training.
17
Total106

Baseline characteristics

CharacteristicExplicit TrainingNo TrainingClassroom TrainingClassroom and Incidental TrainingClassroom and Explicit TrainingIncidental TrainingTotal
Age, Categorical
<=18 years
0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants
Age, Categorical
>=65 years
0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants
Age, Categorical
Between 18 and 65 years
17 Participants19 Participants17 Participants18 Participants17 Participants18 Participants106 Participants
Age, Continuous21.1 years
STANDARD_DEVIATION 2.37
19.8 years
STANDARD_DEVIATION 2.29
20.9 years
STANDARD_DEVIATION 2.66
20.6 years
STANDARD_DEVIATION 2.4
20.6 years
STANDARD_DEVIATION 3.43
20.5 years
STANDARD_DEVIATION 3.07
20.8 years
STANDARD_DEVIATION 2.7
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants
Race (NIH/OMB)
Asian
5 Participants6 Participants7 Participants8 Participants7 Participants7 Participants40 Participants
Race (NIH/OMB)
Black or African American
1 Participants1 Participants2 Participants1 Participants2 Participants2 Participants9 Participants
Race (NIH/OMB)
More than one race
1 Participants1 Participants1 Participants2 Participants2 Participants0 Participants7 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants0 Participants
Race (NIH/OMB)
Unknown or Not Reported
1 Participants2 Participants0 Participants0 Participants0 Participants1 Participants4 Participants
Race (NIH/OMB)
White
9 Participants9 Participants7 Participants7 Participants6 Participants8 Participants46 Participants
Region of Enrollment
United States
17 participants19 participants17 participants18 participants17 participants18 participants106 participants
Sex: Female, Male
Female
11 Participants10 Participants7 Participants11 Participants8 Participants8 Participants55 Participants
Sex: Female, Male
Male
6 Participants9 Participants10 Participants7 Participants9 Participants10 Participants51 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
EG002
affected / at risk
EG003
affected / at risk
EG004
affected / at risk
EG005
affected / at risk
deaths
Total, all-cause mortality
0 / 180 / 170 / 190 / 170 / 180 / 17
other
Total, other adverse events
0 / 180 / 170 / 190 / 170 / 180 / 17
serious
Total, serious adverse events
0 / 180 / 170 / 190 / 170 / 180 / 17

Outcome results

Primary

Change in Auditory Category Learning Accuracy After 2 Months of Training

Each participant's 96 auditory categorization data points at Pre-test and Post-test, respectively, were turned into a mean of the correct answers. The difference between the two accuracy scores represents the mean change in accuracy.

Time frame: Pre-test (baseline) and immediately after 2 months of training.

ArmMeasureValue (MEAN)Dispersion
Incidental TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.43 percentage of correct trialsStandard Deviation 0.19
Explicit TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.31 percentage of correct trialsStandard Deviation 0.26
No TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.04 percentage of correct trialsStandard Deviation 0.11
Classroom TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.48 percentage of correct trialsStandard Deviation 0.2
Classroom and Incidental TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.44 percentage of correct trialsStandard Deviation 0.13
Classroom and Explicit TrainingChange in Auditory Category Learning Accuracy After 2 Months of Training.49 percentage of correct trialsStandard Deviation 0.21
Primary

Change in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training

Each participant's 96 auditory discrimination data points at Pre-test and Post-test, respectively, were reduced to one sensitivity score: d-prime (d': hits minus false alarms). This transformation takes into account response bias and approaches a normal distribution. A higher score represents greater sensitivity. The difference in scores from pre- to post-test represents the change.

Time frame: Pre-test (baseline) and immediately after 2 months of training.

ArmMeasureValue (MEAN)Dispersion
Incidental TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training1.51 sensitivity (d-prime)Standard Deviation 1.36
Explicit TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training0.47 sensitivity (d-prime)Standard Deviation 1.51
No TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training0.53 sensitivity (d-prime)Standard Deviation 0.96
Classroom TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training1.33 sensitivity (d-prime)Standard Deviation 1.68
Classroom and Incidental TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training1.33 sensitivity (d-prime)Standard Deviation 1.32
Classroom and Explicit TrainingChange in Sensitivity (D-prime) to Novel Speech Sounds After 2 Months of Training1.23 sensitivity (d-prime)Standard Deviation 1.12
Primary

Novel Auditory Word Learning Accuracy After 2 Months of Training

At post-test, participants did a three day novel word learning task. Their 48 word identification data points on the first and third days, respectively, were turned into a mean correct score. The difference in scores from Day 1 to Day 3 represents the change in mean novel word learning accuracy.

Time frame: Immediately after 2 months of training.

ArmMeasureValue (MEAN)Dispersion
Incidental TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training.06 percentage of correct trialsStandard Deviation 0.24
Explicit TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training0 percentage of correct trialsStandard Deviation 0.12
No TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training-.03 percentage of correct trialsStandard Deviation 0.16
Classroom TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training-.04 percentage of correct trialsStandard Deviation 0.13
Classroom and Incidental TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training.1 percentage of correct trialsStandard Deviation 0.2
Classroom and Explicit TrainingNovel Auditory Word Learning Accuracy After 2 Months of Training.09 percentage of correct trialsStandard Deviation 0.12
Secondary

Word Recognition Accuracy in Unrelated Language 3 Months After Training

Three months after training, participants were scheduled to learn words in an unrelated language. Their mean accuracy would be calculated.

Time frame: 3 months post-intervention

Population: This component of the project was cancelled due to the COVID-19 pandemic and no data were collected.

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026