Human evoked cortical activity to signal-to-noise ratio and absolute signal level

Billings, Curtis J.; Tremblay, Kelly L.; Stecker, G. Christopher; Tolin, Wendy M.

doi:10.1016/j.heares.2009.04.002

Cited by 141 publications

(155 citation statements)

References 51 publications

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“…The electrophysiological signal was the speech syllable /ba/ that was a naturally produced female exemplar from the UCLA Nonsense Syllable Test (Dubno and Schaefer 1992) shortened to 450 ms by windowing the steady vowel offset of the stimulus. While previous CAEP research focusing on signal level and SNR effects used 1,000-Hz pure tones (Billings et al 2009), a short consonant-vowel speech token provided an ideal CAEP stimulus while providing better face validity when comparing to behavioral speech perception measures. The behavioral signal consisted of Institute of Electrical and Electronic Engineers (IEEE) sentences (IEEE 1969) produced by a female talker.…”

Section: Stimulimentioning

confidence: 99%

“…Existing data demonstrate that SNR, rather than tonal signal level, is a key factor affecting CAEPs recorded in noise (Billings et al 2009). The current study extends those findings to speech stimuli presented at a larger range of signal levels.…”

Section: Electrophysiologymentioning

confidence: 99%

“…Previous research demonstrates that signal-to-noise ratio (SNR) is a major contributor to the physiological processing of signals in noise (Phillips 1990;Billings et al 2009;Whiting et al 1998;Kaplan-Neeman et al 2006). In addition, a long history of psychophysical studies demonstrates the importance of SNR to the perception of sounds (Hawkins and Stevens 1950;Stevens and Guirao 1967).…”

Section: Introductionmentioning

confidence: 99%

“…Several psychophysical studies also indicate that signal level plays an important role in perception in noise by demonstrating that signal level has a small but significant effect on accuracy when SNR is held constant (Summers and Molis 2004;Studebaker et al 1999;Hornsby et al 2005). In contrast, signal level was not a significant contributor to cortical-level processing (Billings et al 2009). Billings et al (2009) recorded cortical auditory evoked potentials (CAEPs) to 1,000-Hz tones presented in continuous background noise and demonstrated that N1 and P2 waves are primarily dependent upon SNR rather than signal level.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, signal level was not a significant contributor to cortical-level processing (Billings et al 2009). Billings et al (2009) recorded cortical auditory evoked potentials (CAEPs) to 1,000-Hz tones presented in continuous background noise and demonstrated that N1 and P2 waves are primarily dependent upon SNR rather than signal level. While N1 and P2 are thought to be obligatory neural responses that are dependent upon the acoustics of the stimulus, the effect of signal level was absent or greatly diminished when signals were presented in noise.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Predicting Perception in Noise Using Cortical Auditory Evoked Potentials

Billings

McMillan

Penman

et al. 2013

JARO

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Speech perception in background noise is a common challenge across individuals and health conditions (e.g., hearing impairment, aging, etc.). Both behavioral and physiological measures have been used to understand the important factors that contribute to perception-in-noise abilities. The addition of a physiological measure provides additional information about signal-in-noise encoding in the auditory system and may be useful in clarifying some of the variability in perception-in-noise abilities across individuals. Fifteen young normal-hearing individuals were tested using both electrophysiology and behavioral methods as a means to determine (1) the effects of signal-tonoise ratio (SNR) and signal level and (2) how well cortical auditory evoked potentials (CAEPs) can predict perception in noise. Three correlation/regression approaches were used to determine how well CAEPs predicted behavior. Main effects of SNR were found for both electrophysiology and speech perception measures, while signal level effects were found generally only for speech testing. These results demonstrate that when signals are presented in noise, sensitivity to SNR cues obscures any encoding of signal level cues. Electrophysiology and behavioral measures were strongly correlated. The best physiological predictors (e.g., latency, amplitude, and area of CAEP waves) of behavior (SNR at which 50 % of the sentence is understood) were N1 latency and N1 amplitude measures. In addition, behavior was best predicted by the 70-dB signal/5-dB SNR CAEP condition. It will be important in future studies to determine the relationship of electrophysiology and behavior in populations who experience difficulty understanding speech in noise such as those with hearing impairment or age-related deficits.

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Section: Stimulimentioning

confidence: 99%

Section: Electrophysiologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predicting Perception in Noise Using Cortical Auditory Evoked Potentials

Billings

McMillan

Penman

et al. 2013

JARO

Self Cite

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show abstract

Communicating in Challenging Environments: Noise and Reverberation

Bidelman

2017

Springer Handbook of Auditory Research

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The effect of hyperarticulation on speech comprehension under adverse listening conditions

Kangatharan

Uther

Gobet

2021

Psychological Research

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Comprehension assesses a listener’s ability to construe the meaning of an acoustic signal in order to be able to answer questions about its contents, while intelligibility indicates the extent to which a listener can precisely retrieve the acoustic signal. Previous comprehension studies asking listeners for sentence-level information or narrative-level information used native listeners as participants. This is the first study to look at whether clear speech properties (e.g. expanded vowel space) produce a clear speech benefit at the word level for L2 learners for speech produced in naturalistic settings. This study explored whether hyperarticulated speech was more comprehensible than non-hyperarticulated speech for both L1 British English speakers and early and late L2 British English learners in quiet and in noise. Sixteen British English listeners, 16 native Mandarin Chinese listeners as early learners of L2 and 16 native Mandarin Chinese listeners as late learners of L2 rated hyperarticulated samples versus non-hyperarticulated samples in form of words for comprehension under four listening conditions of varying white noise level (quiet or SNR levels of + 16 dB, + 12 dB or + 8 dB) (3 × 2× 4 mixed design). Mean ratings showed all three groups found hyperarticulated speech samples easier to understand than non-hyperarticulated speech at all listening conditions. Results are discussed in terms of other findings (Uther et al., 2012) that suggest that hyperarticulation may generally improve speech processing for all language groups.

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Human evoked cortical activity to signal-to-noise ratio and absolute signal level

Cited by 141 publications

References 51 publications

Predicting Perception in Noise Using Cortical Auditory Evoked Potentials

Predicting Perception in Noise Using Cortical Auditory Evoked Potentials

Communicating in Challenging Environments: Noise and Reverberation

The effect of hyperarticulation on speech comprehension under adverse listening conditions

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