Acoustic Background Research Articles

Acoustics and activity noise in school classrooms in Finland

School classrooms are learning spaces for children and workplaces where a teacher’s most important tool, his or her voice, is subjected to considerable loading. Because noise has several detrimental effects on human functioning including speech production and perception, a noiseless environment and good acoustics in classrooms are important. The main aim of this study was to investigate the classroom as a sound environment and to ascertain the effect of acoustics.Activity noise levels, background noise levels and acoustics were measured in school classrooms (N=40), and the associations between these were studied. The acoustics of measured in these classrooms were compared to the values of the Finnish national standard. Acoustic parameters (reverberation time and Speech Transmission Index, STI) and background noise levels were measured in unoccupied classrooms and activity noise levels were measured during classroom instruction.The results showed that only few classrooms fulfilled the acoustic criteria of the Finnish national standard and no classroom fulfilled the criterion for acoustics measured according to the STI. In most of the classrooms the background noise level was higher than recommended and activity noise levels were high for listening and communication. According to the results, the acoustic environment in these school classrooms was detrimental to speech communication and learning. This also implies a risk of occupational voice disorders. Acoustic ergonomics should be taken into account and acoustic standards should to be fulfilled when new schools are built and old ones refurbished.

Multiscale analysis of the acoustic scattering by many scatterers of impedance type

We are concerned with the acoustic scattering problem, at a frequency $\kappa$, by many small obstacles of arbitrary shapes with impedance boundary condition. These scatterers are assumed to be included in a bounded domain $\Omega$ in $\mathbb{R}^3$ which is embedded in an acoustic background characterized by an eventually locally varying index of refraction. The collection of the scatterers $D_m, \; m=1,...,M$ is modeled by four parameters: their number $M$, their maximum radius $a$, their minimum distance $d$ and the surface impedances $\lambda_m, \; m=1,...,M$. We consider the parameters $M, d$ and $\lambda_m$'s having the following scaling properties: $M:=M(a)=O(a^{-s})$, $d:=d(a)\approx a^t$ and $\lambda_m:=\lambda_m(a)=\lambda_{m,0}a^{-\beta}$, as $a \rightarrow 0$, with non negative constants $s, t$ and $\beta$ and complex numbers $\lambda_{m, 0}$'s with eventually negative imaginary parts. We derive the asymptotic expansion of the farfields with explicit error estimate in terms of $a$, as $a\rightarrow 0$. The dominant term is the Foldy-Lax field corresponding to the scattering by the point-like scatterers located at the centers $z_m$'s of the scatterers $D_m$'s with $\lambda_m \vert \partial D_m\vert$ as the related scattering coefficients.

Generation of the low-frequency branch of acoustic emission in affected rocks

As follows from data analysis of physical modeling, the reaction of acoustic background oscillations to an external impact is well-defined under triaxial loading of a dry sandstone core in the low-frequency range (1–100 Hz). This phenomenon is explained by the generation of a low-frequency constituent of acoustic emission. A high correlation of oscillation dynamics (Klimontovich S entropy) is observed at frequencies of tens of hertz and tens of kilohertz in the absence of such a correlation in the intermediate frequency range; a synchronous increase in the oscillation level is also observed at low and high frequencies.

Lionello Sozzi e la sua esperienza della musica

Lionello Sozzi’s relationship with music wasn’t the outcome of an intellectual pursuit; it was, rather, instinctive and direct, to the point that music became the acoustic background of his very life. This naturalness is confirmed by the way his passion for music was born and grew: at first within his family and later on in meetings with friends who happened to be musicians and in fortuitous encounters, almost never along the traditional avenues of concert halls and opera-houses. Sozzi was fond of saying of himself that he was “just a lover of music”, but he would talk about music with a flair that revealed deep acumen and mature connoisseurship, especially evident in his autobiographical volume Why I love music and in his essays written for the Teatro Regio of Turin. In them his familiarity with literary sources, such as Goethe, Mérimée, Anatole France and Beaumarchais, opened the way to fresh interpretations of musical works deriving from them. The amount of music taken into consideration, including songs, is a concrete proof of the capital role Enlightenment and French culture of the xviiith century played in shaping Sozzi’s intellectual personality; at the same time his unending listening to music sheds light on the depth of his sensibility, which couldn’t but lead towards the shores of “décadence” and of modernity.

Spatial Angular Compounding of Photoacoustic Images.

Photoacoustic (PA) images utilize pulsed lasers and ultrasound transducers to visualize targets with higher optical absorption than the surrounding medium. However, they are susceptible to acoustic clutter and background noise artifacts that obfuscate biomedical structures of interest. We investigated three spatial-angular compounding methods to improve PA image quality for biomedical applications, implemented by combining multiple images acquired as an ultrasound probe was rotated about the elevational axis with the laser beam and target fixed. Compounding with conventional averaging was based on the pose information of each PA image, while compounding with weighted and selective averaging utilized both the pose and image content information. Weighted-average compounding enhanced PA images with the least distortion of signal size, particularly when there were large (i.e., 2.5 mm and 7 (°)) perturbations from the initial probe position. Selective-average compounding offered the best improvement in image quality with up 181, 1665, and 1568 times higher contrast, CNR, and SNR, respectively, compared to the mean values of individual PA images. The three presented spatial compounding methods have promising potential to enhance image quality in multiple photoacoustic applications.

Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

Evaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier are introduced. The sound source localization algorithm based on the analysis of multichannel signals from the Acoustic Vector Sensor is presented. The methods are evaluated in an experiment conducted in the anechoic chamber, in which the representative events are played together with noise of differing intensity. The results of detection, classification and localization accuracy with respect to the Signal to Noise Ratio are discussed. The results show that the recognition and localization accuracy are strongly dependent on the acoustic conditions. We also found that the engineered algorithms provide a sufficient robustness in moderately intense noise in order to be applied to practical audio-visual surveillance systems.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.

Background Noise Degrades Central Auditory Processing in Toddlers.

Noise, as an unwanted sound, has become one of modern society's environmental conundrums, and many children are exposed to higher noise levels than previously assumed. However, the effects of background noise on central auditory processing of toddlers, who are still acquiring language skills, have so far not been determined. The authors evaluated the effects of background noise on toddlers' speech-sound processing by recording event-related brain potentials. The hypothesis was that background noise modulates neural speech-sound encoding and degrades speech-sound discrimination. Obligatory P1 and N2 responses for standard syllables and the mismatch negativity (MMN) response for five different syllable deviants presented in a linguistic multifeature paradigm were recorded in silent and background noise conditions. The participants were 18 typically developing 22- to 26-month-old monolingual children with healthy ears. The results showed that the P1 amplitude was smaller and the N2 amplitude larger in the noisy conditions compared with the silent conditions. In the noisy condition, the MMN was absent for the intensity and vowel changes and diminished for the consonant, frequency, and vowel duration changes embedded in speech syllables. Furthermore, the frontal MMN component was attenuated in the noisy condition. However, noise had no effect on P1, N2, or MMN latencies. The results from this study suggest multiple effects of background noise on the central auditory processing of toddlers. It modulates the early stages of sound encoding and dampens neural discrimination vital for accurate speech perception. These results imply that speech processing of toddlers, who may spend long periods of daytime in noisy conditions, is vulnerable to background noise. In noisy conditions, toddlers' neural representations of some speech sounds might be weakened. Thus, special attention should be paid to acoustic conditions and background noise levels in children's daily environments, like day-care centers, to ensure a propitious setting for linguistic development. In addition, the evaluation and improvement of daily listening conditions should be an ordinary part of clinical intervention of children with linguistic problems.

Robust Maximum Likelihood Acoustic Energy Based Source Localization in Correlated Noisy Sensing Environments

Acoustic energy based localization with wireless sensor networks is an interesting solution to locate sources and targets. For simplicity, localization formulation based on the maximum likelihood (ML) approach considers that the source and noise samples are uncorrelated and represented by a Gaussian distribution. However, the acoustic background noise can severely affect the accuracy of the location estimation. This paper proposes an accurate error estimate in which the correlation of the received signals at each wireless sensor is represented by a Hurst exponent and modeled by a fractional Gaussian noise (fGn). The experimental results show that the proposed solution is more appropriate for the source localization estimation under real acoustic noises and even for highly non-stationary sources.

Modality of fear cues affects acoustic startle potentiation but not heart-rate response in patients with dental phobia

The acoustic startle response (SR) has consistently been shown to be enhanced by fear-arousing cross-modal background stimuli in phobics. Intra-modal fear-potentiation of acoustic SR was rarely investigated and generated inconsistent results. The present study compared the acoustic SR to phobia-related sounds with that to phobia-related pictures in 104 dental phobic patients and 22 controls. Acoustic background stimuli were dental treatment noises and birdsong and visual stimuli were dental treatment and neutral control pictures. Background stimuli were presented for 4 s, randomly followed by the administration of the startle stimulus. In addition to SR, heart-rate (HR) was recorded throughout the trials. Irrespective of their content, background pictures elicited greater SR than noises in both groups with a trend for phobic participants to show startle potentiation to phobia-related pictures but not noises. Unlike controls, phobics showed HR acceleration to both dental pictures and noises. HR acceleration of the phobia group was significantly positively correlated with SR in the noise condition only. The acoustic SR to phobia-related noises is likely to be inhibited by prolonged sensorimotor gating.

A survey of acoustic conditions and noise levels in secondary school classrooms in England.

An acoustic survey of secondary schools in England has been undertaken. Room acoustic parameters and background noise levels were measured in 185 unoccupied spaces in 13 schools to provide information on the typical acoustic environment of secondary schools. The unoccupied acoustic and noise data were correlated with various physical characteristics of the spaces. Room height and the amount of glazing were related to the unoccupied reverberation time and therefore need to be controlled to reduce reverberation to suitable levels for teaching and learning. Further analysis of the unoccupied data showed that the introduction of legislation relating to school acoustics in England and Wales in 2003 approximately doubled the number of school spaces complying with current standards. Noise levels were also measured during 274 lessons to examine typical levels generated during teaching activities in secondary schools and to investigate the influence of acoustic design on working noise levels in the classroom. Comparison of unoccupied and occupied data showed that unoccupied acoustic conditions affect the noise levels occurring during lessons. They were also related to the time spent in disruption to the lessons (e.g., students talking or shouting) and so may also have an impact upon student behavior in the classroom.

The Implementation Of High Efficiency Wireless Sensor In Acoustic Object Tracking

Abstract Energy control in Wireless Sensor Network is one of the most crucial technologies. Based on the acoustic object localization background, we designed a new structure of the sensor node to realize the energy efficiency in the power supply and artificial sleeping scheduling in this paper. The power control model is independent with data processing and control model and can separately realize the power supply for different part of the node. The node can transfer status according the different circumstance to minimize the energy consumption. Furthermore, a new synchronous sleeping/wake schedule mechanism in the medium access control layer is proposed. Sensor nodes can use the forwarding and listening status to schedule their better energy status on demanded. The experiment has been evaluated and analyzed in a test-bed. The result confirms the structure and the proposed mechanism are energy efficiency and gain better trade-off between the accuracy and efficiency

Acoustic environment identification using unsupervised learning

Acoustic environment leaves its characteristic signature in the audio recording captured in it. The acoustic environment signature can be modeled using acoustic reverberations and background noise. Acoustic reverberation depends on the geometry and composition of the recording location. The proposed scheme uses similarity in the estimated acoustic signature for acoustic environment identification (AEI). We describe a parametric model to realize acoustic reverberation, and a statistical framework based on maximum likelihood estimation is used to estimate the model parameters. The density-based clustering is used for automatic AEI using estimated acoustic parameters. Performance of the proposed framework is evaluated for two data sets consisting of hand-clapping and speech recordings made in a diverse set of acoustic environments using three microphones. Impact of the microphone type variation, frequency, and clustering accuracy and efficiency on the performance of the proposed method is investigated. Performance of the proposed method is also compared with the existing state-of-the-art (SoA) for AEI.

Super-Audible Voice Activity Detection

In this paper, reflected sound of frequency just above the audible range is used to detect speech activity. The active signal used is inaudible to humans, readily generated by the typical audio circuitry and components found in mobile telephones, and is robust to background sounds such as nearby voices. In use, the system relies upon a wideband excitation signal emitted from a loudspeaker located near the lips, which reflects from the mouth region and is then captured by a nearby microphone. The state of the lip opening is evaluated periodically by tracking the resonance patterns in the reflected excitation signal. When the lips are open, deep and complex resonances are formed as energy propagates into and then reflects out from the open mouth and vocal tract, with resonance depth being related to the open lip area. When the lips are closed, these resonance patterns are absent. The presence of the resonances can thus serve as a low complexity detection measure. The technique is evaluated for multiple users in terms of sensitivity to source placement and sensor placement. Voice activity detection performance using this measure is further evaluated in the presence of realistic wideband acoustic background noise, as well as artificially added noise. The system is shown to be relatively insensitive to sensor placement, highly insensitive to background noise, and able to achieve greater than 90% voice activity detection accuracy. The technique is even suitable when a subject is whispering in the presence of much louder multi-speaker babble. The technique has potential for speech-based systems operating in high noise environments as well as in silent speech interfaces, whisper-input systems and voice prostheses for speech-impaired users.

A Time Series Sodar Simulator Based on Large-Eddy Simulation

Abstract A sodar simulator capable of producing time series data emulating sodar signals has been developed and tested. The atmospheric fields used to populate the sodar simulator are taken from output of a large-eddy simulation code. The characteristics of the sodar (number and zenith angle of beams, beamwidth, transmit frequency, range resolution, etc.) are defined by the user to allow emulation of existing systems. The range of the reflected acoustic signal is calculated based upon a temperature-dependent speed of sound. Realistic acoustic background noise is simulated using filtered white noise. The raw acoustic time series data are processed using a Fourier transform to yield acoustic Doppler spectra, from which the radial velocities are calculated. The design of the simulator allows for the testing of and comparisons between various signal-processing techniques and averaging periods. An example case of feeding the sodar simulator with large-eddy simulation data representative of a developing convective boundary layer is presented and discussed.

Auditory cortex extraction of attended speech envelope in a multi-talker background

Event Abstract Back to Event Auditory cortex extraction of attended speech envelope in a multi-talker background Marc Vander Ghinst1*, Mathieu Bourguignon1, Marc Op De Beeck1, Vincent Wens1, Brice Marty1, Sergio Hassid2, Georges Choufani2, Veikko Jousmäki3, Riitta Hari3, Patrick Van Bogaert1, Serge Goldman1 and Xavier De Tiège1 1 Université Libre de Bruxelles, Belgium 2 Hopital Erasme - Clinique Universitaires de Bruxelles, ENT, Belgium 3 Aalto University School of Science, Finland Introduction and Aim: To understand a single speaker when other competing voices are present, the auditory system needs to handle multiple kinds of acoustic cues. Among those different acoustic cues, the temporal envelope has been identified as a contributor to speech in noise perception. The aim of this study was to evaluate, using a continuous listening paradigm, the impact of noise on the cortical representation of speech temporal envelope. Material and methods: Magnetoencephalographic (MEG) signals were recorded from 20 adult listeners. Subjects were asked to listen to 5 different recorded texts read in French. Different levels of noise (cocktail party type) were randomly added to four recordings with the following signal to noise ratio: +5, 0, -5 and -10 dB. The coherence between subjects' MEG signals and the heard sounds (speakers' voice+noise), speakers’ voice (speakers only) or noise only was computed at the sensor level to index the level of coupling in the different noise conditions. Coherent sources were identified using minimum norm estimation. Results: At sensor level, coherence was observed with speaker’s voice at around 0.5 Hz. Without noise, the most coherent brain regions with the speakers’ voice were located at the posterior superior temporal sulcus (pSTS), with a right-hemisphere predominance. Coherence levels at the pSTS were significantly higher with speakers’ voice than with the heard sounds (p<0.05, non-parametric permutation test). Coherence with the speakers’ voice decreased significantly with the noise level (p<0.01, two-way ANOVA). With increasing noise level, the coherence decreased more rapidly at the right pSTS, so that coherence was left-lateralized in presence of noise. Conclusions: This study demonstrates that neurons in non-primary auditory areas extract attended speech envelope from the acoustic background, up to a certain noise level. When noise progressively merged into speech, a left-lateralized phase-coupling is observed between pSTS neural activity and speakers’ voice. Keywords: Speech in noise, Magnetoencephalography (MEG), Speech Perception, auditory processing, Auditory Cortex Conference: Belgian Brain Council 2014 MODULATING THE BRAIN: FACTS, FICTION, FUTURE, Ghent, Belgium, 4 Oct - 4 Oct, 2014. Presentation Type: Poster Presentation Topic: Basic Neuroscience Citation: Vander Ghinst M, Bourguignon M, Op De Beeck M, Wens V, Marty B, Hassid S, Choufani G, Jousmäki V, Hari R, Van Bogaert P, Goldman S and De Tiège X (2014). Auditory cortex extraction of attended speech envelope in a multi-talker background. Conference Abstract: Belgian Brain Council 2014 MODULATING THE BRAIN: FACTS, FICTION, FUTURE. doi: 10.3389/conf.fnhum.2014.214.00020 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 27 Jun 2014; Published Online: 30 Jun 2014. * Correspondence: Dr. Marc Vander Ghinst, Université Libre de Bruxelles, Brussels, Belgium, marcvdg@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Marc Vander Ghinst Mathieu Bourguignon Marc Op De Beeck Vincent Wens Brice Marty Sergio Hassid Georges Choufani Veikko Jousmäki Riitta Hari Patrick Van Bogaert Serge Goldman Xavier De Tiège Google Marc Vander Ghinst Mathieu Bourguignon Marc Op De Beeck Vincent Wens Brice Marty Sergio Hassid Georges Choufani Veikko Jousmäki Riitta Hari Patrick Van Bogaert Serge Goldman Xavier De Tiège Google Scholar Marc Vander Ghinst Mathieu Bourguignon Marc Op De Beeck Vincent Wens Brice Marty Sergio Hassid Georges Choufani Veikko Jousmäki Riitta Hari Patrick Van Bogaert Serge Goldman Xavier De Tiège PubMed Marc Vander Ghinst Mathieu Bourguignon Marc Op De Beeck Vincent Wens Brice Marty Sergio Hassid Georges Choufani Veikko Jousmäki Riitta Hari Patrick Van Bogaert Serge Goldman Xavier De Tiège Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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A dual contribution to the involuntary semantic processing of unexpected spoken words.

Sounds are a major cause of distraction. Unexpected to-be-ignored auditory stimuli presented in the context of an otherwise repetitive acoustic background ineluctably break through selective attention and distract people from an unrelated visual task (deviance distraction). This involuntary capture of attention by deviant sounds has been hypothesized to trigger their semantic appraisal and, in some circumstances, interfere with ongoing performance, but it remains unclear how such processing compares with the automatic processing of distractors in classic interference tasks (e.g., Stroop, flanker, Simon tasks). Using a cross-modal oddball task, we assessed the involuntary semantic processing of deviant sounds in the presence and absence of deviance distraction. The results revealed that some involuntary semantic analysis of spoken distractors occurs in the absence of deviance distraction but that this processing is significantly greater in its presence. We conclude that the automatic processing of spoken distractors reflects 2 contributions, one that is contingent upon deviance distraction and one that is independent from it.

Audio Recording Location Identification Using Acoustic Environment Signature

An audio recording is subject to a number of possible distortions and artifacts. Consider, for example, artifacts due to acoustic reverberation and background noise. The acoustic reverberation depends on the shape and the composition of the room, and it causes temporal and spectral smearing of the recorded sound. The background noise, on the other hand, depends on the secondary audio source activities present in the evidentiary recording. Extraction of acoustic cues from an audio recording is an important but challenging task. Temporal changes in the estimated reverberation and background noise can be used for dynamic acoustic environment identification (AEI), audio forensics, and ballistic settings. We describe a statistical technique based on spectral subtraction to estimate the amount of reverberation and nonlinear filtering based on particle filtering to estimate the background noise. The effectiveness of the proposed method is tested using a data set consisting of speech recordings of two human speakers (one male and one female) made in eight acoustic environments using four commercial grade microphones. Performance of the proposed method is evaluated for various experimental settings such as microphone independent, semi- and full-blind AEI, and robustness to MP3 compression. Performance of the proposed framework is also evaluated using Temporal Derivative-based Spectrum and Mel-Cepstrum (TDSM)-based features. Experimental results show that the proposed method improves AEI performance compared with the direct method (i.e., feature vector is extracted from the audio recording directly). In addition, experimental results also show that the proposed scheme is robust to MP3 compression attack.

Acoustic Environment Identification and Its Applications to Audio Forensics

An audio recording is subject to a number of possible distortions and artifacts. Consider, for example, artifacts due to acoustic reverberation and background noise. The acoustic reverberation depends on the shape and the composition of a room, and it causes temporal and spectral smearing of the recorded sound. The background noise, on the other hand, depends on the secondary audio source activities present in the evidentiary recording. Extraction of acoustic cues from an audio recording is an important but challenging task. Temporal changes in the estimated reverberation and background noise can be used for dynamic acoustic environment identification (AEI), audio forensics, and ballistic settings. We describe a statistical technique to model and estimate the amount of reverberation and background noise variance in an audio recording. An energy-based voice activity detection method is proposed for automatic decaying-tail-selection from an audio recording. Effectiveness of the proposed method is tested using a data set consisting of speech recordings. The performance of the proposed method is also evaluated for both speaker-dependent and speaker-independent scenarios.

POZIOM NATĘŻENIA GŁOSU WYKŁADOWCÓW - WYNIKI BADAŃ PRZEPROWADZONYCH PODCZAS WYKŁADÓW

Occupational voice users (inter alia: lecturers) speak with different levels of vocal intensity. Speakers adjust this intensity knowingly (e.g. to underline the importance of fragments of the speech) or unknowingly. The unknown adjustment of voice intensity occurs e.g. in the presence of high acoustic background noise (so-called Lombard effect), but it also results from many other factors: hearing loss, construction of the vocal tract, habits and others. The aim of the article is to confirm the thesis that in similar conditions of acoustic properties of the room different lecturers speak with different levels of vocal intensity. The study was conducted in a group of 10 lecturers in the same conference room. A-weighted sound pressure level determined at 1 m from the lecturer's mouth was adopted as a parameter defining the intensity of the lecturer's voice. The levels of all lecturers' voice intensity were compared and evaluated according to the criteria defined in EN ISO 9921. Nine in ten lecturers were speaking with normal voice intensity (60-65 dB) and only one full-time university lecturer was speaking with raised voice (66-71 dB). It was found that in the room of the same acoustic conditions the lecturers spoke with different intensities of voice. Some lecturers occasionally, and one all the time spoke with the voice intensity specified by PN-EN ISO 9921 as a raised voice. The results of the preliminary study warrant further studies in a larger group of teachers.