Speaking in noise: How does the Lombard effect improve acoustic contrasts between speech and ambient noise?

Garnier, Maëva; Henrich, Nathalie

doi:10.1016/j.csl.2013.07.005

Cited by 102 publications

(87 citation statements)

References 37 publications

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“…For both genders, these results showed a strong positive correlation between background noise level and voice SPL, which is in line with past findings 16,30,31 and reflects the Lombard effect. We assume that, for the sake of intelligibility, teachers raise their voice in response to increased background noise.…”

Section: Discussionsupporting

confidence: 92%

“…16,32 This correlation was stronger in males than females and could represent another automatic strategy to make oneself understood over background noise. Similarly, Garnier and Henrich 16 found that, regardless of the type of noise presented, speakers not only spoke louder but tended to prolong voiced speech sounds as well. This effect was measured for voiced consonants but was particularly strong for vowels.…”

Section: Discussionmentioning

confidence: 99%

“…27 Such dysfunctions may arise when speakers increase their voice SPL and F0 in the presence of background noise -a phenomenon known as the Lombard effect. 16,28 Indeed, research suggests that music teachers, whose principal instrument is their voice, are particularly likely to develop voice disorders. 29 Against this background, it can be assumed that the population of music theory teachers constitutes a high-risk group as well.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, background noise level may also influence vocal loading, as it automatically causes speakers to increase their voice SPL and F0 or modulate spectral aspects. 16,17 workday. This allows one to present an authentic picture of both professional and extra-professional vocal demands.…”

Section: Introductionmentioning

confidence: 99%

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Voice Use Among Music Theory Teachers: A Voice Dosimetry and Self-Assessment Study

2018

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Objectives: (1) To investigate music theory teachers' professional and extra-professional vocal loading and background noise exposure, (2) to determine the correlation between vocal loading and background noise, and (3) to determine the correlation between vocal loading and self-evaluation data.Methods: Using voice dosimetry, 13 music theory teachers were monitored for one workweek.Parameters analysed were voice SPL, F0, phonation time, vocal loading index (VLI) and noise SPL.Spearman's correlation was used to correlate vocal loading parameters (voice SPL, F0 and phonation time) and noise SPL. Each day, subjects self-assessed their voice using visual analogue scales. VLI and self-evaluation data were correlated using Spearman's correlation.Results: Vocal loading parameters and noise SPL were significantly higher in the professional than in the extra-professional environment. Voice SPL, phonation time and females' F0 correlated positively with noise SPL. VLI correlated with self-assessed voice quality, vocal fatigue and amount of singing and speaking voice produced. Conclusions:Teaching music theory is a profession with high vocal demands. More background noise is associated with increased vocal loading and may indirectly increase the risk for voice disorders.Correlations between VLI and self-assessments suggest that these teachers are well-aware of their vocal demands and feel their effect on voice quality and vocal fatigue. Visual analogue scales seem to represent a useful tool for subjective vocal loading assessment and associated symptoms in these professional voice users.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Voice Use Among Music Theory Teachers: A Voice Dosimetry and Self-Assessment Study

2018

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“…Past studies have observed changes in energy distribution across phone classes, flattening of the spectral slope, upward shifts of formant center frequencies, and changes in formant bandwidths when comparing whispered speech to neutral [1-4, 8, 11], effects in many ways similar to those in stressed and Lombard effect speech [13][14][15][16][17][18][19]. To verify the energy and slope effects in the VEII database, we analyze distributions of the first two cepstral coefficients c0 and c1 in the MFCC front-end [20].…”

Section: Neutral/whispered Speech Analysismentioning

confidence: 99%

UT-Vocal Effort II: Analysis and constrained-lexicon recognition of whispered speech

Ghaffarzadegan

Bořil

Hansen

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This study focuses on acoustic variations in speech introduced by whispering, and proposes several strategies to improve robustness of automatic speech recognition of whispered speech with neutral-trained acoustic models. In the analysis part, differences in neutral and whispered speech captured in the UT-Vocal Effort II corpus are studied in terms of energy, spectral slope, and formant center frequency and bandwidth distributions in silence, voiced, and unvoiced speech signal segments. In the part dedicated to speech recognition, several strategies involving front-end filter bank redistribution, cepstral dimensionality reduction, and lexicon expansion for alternative pronunciations are proposed. The proposed neutral-trained system employing redistributed filter bank and reduced features provides a 7.7 % absolute WER reduction over the baseline system trained on neutral speech, and a 1.3 % reduction over a baseline system with whisper-adapted acoustic models.

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An examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!

Elvevåg

Cohen

Wolters

et al. 2016

American J of Med Genetics Pt B

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The National Institute of Mental Health's Research Domain Criteria (RDoC) Initiative “calls for the development of new ways of classifying psychopathology based on dimensions of observable behavior.” As a result of this ambitious initiative, language has been identified as an independent construct in the RDoC matrix. In this article, we frame language within an evolutionary and neuropsychological context and discuss some of the limitations to the current measurements of language. Findings from genomics and the neuroimaging of performance during language tasks are discussed in relation to serious mental illness and within the context of caveats regarding measuring language. Indeed, the data collection and analysis methods employed to assay language have been both aided and constrained by the available technologies, methodologies, and conceptual definitions. Consequently, different fields of language research show inconsistent definitions of language that have become increasingly broad over time. Individually, they have also shown significant improvements in conceptual resolution, as well as in experimental and analytic techniques. More recently, language research has embraced collaborations across disciplines, notably neuroscience, cognitive science, and computational linguistics and has ultimately re‐defined classical ideas of language. As we move forward, the new models of language with their remarkably multifaceted constructs force a re‐examination of the NIMH RDoC conceptualization of language and thus the neuroscience and genetics underlying this concept. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

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Speaking in noise: How does the Lombard effect improve acoustic contrasts between speech and ambient noise?

Cited by 102 publications

References 37 publications

Voice Use Among Music Theory Teachers: A Voice Dosimetry and Self-Assessment Study

Voice Use Among Music Theory Teachers: A Voice Dosimetry and Self-Assessment Study

UT-Vocal Effort II: Analysis and constrained-lexicon recognition of whispered speech

An examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!

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