Speech Recognition in Nonnative versus Native English-Speaking College Students in a Virtual Classroom

2017 ◽  
Vol 28 (05) ◽  
pp. 404-414 ◽  
Author(s):  
Dorothy Neave-DiToro ◽  
Adrienne Rubinstein ◽  
Arlene C. Neuman

Background: Limited attention has been given to the effects of classroom acoustics at the college level. Many studies have reported that nonnative speakers of English are more likely to be affected by poor room acoustics than native speakers. An important question is how classroom acoustics affect speech perception of nonnative college students. Purpose: The combined effect of noise and reverberation on the speech recognition performance of college students who differ in age of English acquisition was evaluated under conditions simulating classrooms with reverberation times (RTs) close to ANSI recommended RTs. Research Design: A mixed design was used in this study. Study Sample: Thirty-six native and nonnative English-speaking college students with normal hearing, ages 18–28 yr, participated. Intervention: Two groups of nine native participants (native monolingual [NM] and native bilingual) and two groups of nine nonnative participants (nonnative early and nonnative late) were evaluated in noise under three reverberant conditions (0.03, 0.06, and 0.08 sec). Data Collection and Analysis: A virtual test paradigm was used, which represented a signal reaching a student at the back of a classroom. Speech recognition in noise was measured using the Bamford–Kowal–Bench Speech-in-Noise (BKB-SIN) test and signal-to-noise ratio required for correct repetition of 50% of the key words in the stimulus sentences (SNR-50) was obtained for each group in each reverberant condition. A mixed-design analysis of variance was used to determine statistical significance as a function of listener group and RT. Results: SNR-50 was significantly higher for nonnative listeners as compared to native listeners, and a more favorable SNR-50 was needed as RT increased. The most dramatic effect on SNR-50 was found in the group with later acquisition of English, whereas the impact of early introduction of a second language was subtler. At the ANSI standard’s maximum recommended RT (0.6 sec), all groups except the NM group exhibited a mild signal-to-noise ratio (SNR) loss. At the 0.8 sec RT, all groups exhibited a mild SNR loss. Conclusion: Acoustics in the classroom are an important consideration for nonnative speakers who are proficient in English and enrolled in college. To address the need for a clearer speech signal by nonnative students (and for all students), universities should follow ANSI recommendations, as well as minimize background noise in occupied classrooms. Behavioral/instructional strategies should be considered to address factors that cannot be compensated for through acoustic design.

2020 ◽  
Author(s):  
chaofeng lan ◽  
yuanyuan Zhang ◽  
hongyun Zhao

Abstract This paper draws on the training method of Recurrent Neural Network (RNN), By increasing the number of hidden layers of RNN and changing the layer activation function from traditional Sigmoid to Leaky ReLU on the input layer, the first group and the last set of data are zero-padded to enhance the effective utilization of data such that the improved reduction model of Denoise Recurrent Neural Network (DRNN) with high calculation speed and good convergence is constructed to solve the problem of low speaker recognition rate in noisy environment. According to this model, the random semantic speech signal with a sampling rate of 16 kHz and a duration of 5 seconds in the speech library is studied. The experimental settings of the signal-to-noise ratios are − 10dB, -5dB, 0dB, 5dB, 10dB, 15dB, 20dB, 25dB. In the noisy environment, the improved model is used to denoise the Mel Frequency Cepstral Coefficients (MFCC) and the Gammatone Frequency Cepstral Coefficents (GFCC), impact of the traditional model and the improved model on the speech recognition rate is analyzed. The research shows that the improved model can effectively eliminate the noise of the feature parameters and improve the speech recognition rate. When the signal-to-noise ratio is low, the speaker recognition rate can be more obvious. Furthermore, when the signal-to-noise ratio is 0dB, the speaker recognition rate of people is increased by 40%, which can be 85% improved compared with the traditional speech model. On the other hand, with the increase in the signal-to-noise ratio, the recognition rate is gradually increased. When the signal-to-noise ratio is 15dB, the recognition rate of speakers is 93%.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4487
Author(s):  
Axel Clouet ◽  
Jérôme Vaillant ◽  
David Alleysson

Digital images are always affected by noise and the reduction of its impact is an active field of research. Noise due to random photon fall onto the sensor is unavoidable but could be amplified by the camera image processing such as in the color correction step. Color correction is expressed as the combination of a spectral estimation and a computation of color coordinates in a display color space. Then we use geometry to depict raw, spectral and color signals and noise. Geometry is calibrated on the physics of image acquisition and spectral characteristics of the sensor to study the impact of the sensor space metric on noise amplification. Since spectral channels are non-orthogonal, we introduce the contravariant signal to noise ratio for noise evaluation at spectral reconstruction level. Having definitions of signal to noise ratio for each steps of spectral or color reconstruction, we compare performances of different types of sensors (RGB, RGBW, RGBWir, CMY, RYB, RGBC).


2013 ◽  
Vol 479-480 ◽  
pp. 1027-1031
Author(s):  
Man Man Guo ◽  
Yun Xue Liu ◽  
Wen Qiang Fan

Spectrum sensing is a crucial issue in cognitive radio networks for primary user detection. Cooperative sensing based on energy detection in the cognitive radio network with multiple antennas base-station is considered in this letter. To improve the sensing performance, we investigate hybrid fusion of the observed energies from the base-station and decisions (1bit, hard information) from different cognitive radio (CR) users around the base-station. Further, we present an optimized scheme where the global detection probability can be maximized according to the Neyman-Pearson criterion. Finally the impact of the change of parameters (Signal to Noise Ratio and number of CR users) in the optimized scheme is analyzed. Numerical simulations and extensive analysis confirm that hybrid fusion base on the optimized scheme is a good choice, also, Signal to Noise Ratio (SNR) and number of CR users does not have influence on the optimized scheme


2020 ◽  
Author(s):  
Reinhardt Rading

<div>This paper investigates the impact on the optical</div><div>signal-to-noise ratio (OSNR) of the residual per span (RDPS) in a N × 100km dispersion managed system with zero total accumulated dispersion from input to output using split step Fourier method (SSFM) -Monte Carlo simulation. </div><div><br></div><div>This paper shows that the nonlinear interference NLI does in-fact impact the performance yielding different best working power depending on the value of Nx100 km span and the type of dispersion managed link. The paper shows that dispersion uncompensated optical links are preferable to dispersion managed fibers in equalizing NLI effects in long haul optical links.</div>


2020 ◽  
Vol 19 ◽  
pp. 153601212091369
Author(s):  
Asmaysinh Gharia ◽  
Efthymios P. Papageorgiou ◽  
Simeon Giverts ◽  
Catherine Park ◽  
Mekhail Anwar

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.


2019 ◽  
Vol 28 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Jenna M. Browning ◽  
Emily Buss ◽  
Mary Flaherty ◽  
Tim Vallier ◽  
Lori J. Leibold

Purpose The purpose of this study was to evaluate speech-in-noise and speech-in-speech recognition associated with activation of a fully adaptive directional hearing aid algorithm in children with mild to severe bilateral sensory/neural hearing loss. Method Fourteen children (5–14 years old) who are hard of hearing participated in this study. Participants wore laboratory hearing aids. Open-set word recognition thresholds were measured adaptively for 2 hearing aid settings: (a) omnidirectional (OMNI) and (b) fully adaptive directionality. Each hearing aid setting was evaluated in 3 listening conditions. Fourteen children with normal hearing served as age-matched controls. Results Children who are hard of hearing required a more advantageous signal-to-noise ratio than children with normal hearing to achieve comparable performance in all 3 conditions. For children who are hard of hearing, the average improvement in signal-to-noise ratio when comparing fully adaptive directionality to OMNI was 4.0 dB in noise, regardless of target location. Children performed similarly with fully adaptive directionality and OMNI settings in the presence of the speech maskers. Conclusions Compared to OMNI, fully adaptive directionality improved speech recognition in steady noise for children who are hard of hearing, even when they were not facing the target source. This algorithm did not affect speech recognition when the background noise was speech. Although the use of hearing aids with fully adaptive directionality is not proposed as a substitute for remote microphone systems, it appears to offer several advantages over fixed directionality, because it does not depend on children facing the target talker and provides access to multiple talkers within the environment. Additional experiments are required to further evaluate children's performance under a variety of spatial configurations in the presence of both noise and speech maskers.


2011 ◽  
Vol 133 (6) ◽  
Author(s):  
M. L. Seto

A ship’s radiated acoustic signature is known after a range measurement, but it changes from that the longer the ship is in-service. The Ship Signatures Management System (SSMS) provides an organic, real-time capability for a naval ship to monitor its own signature in order to evaluate the impact of proposed actions on its counter-detection range and sensor performance. Ship protection is enhanced through insightful and timely signature data. In particular, this paper discusses the tonal detection and tracking algorithms used to monitor on-board machinery and propeller activity. The paper specifically addresses tonals that appear or disappear as a consequence of changes in the background level, as well as that of crossed tonals. This is of significance because it impacts the SSMS’s ability to attribute cause to changes in the ship acoustic signature. In particular, it is impossible to associate tonals that are time synchronized in their frequency and intensity changes as being created by a single cause (e.g., piece of machinery) with a known tonal set. The use of tonal amplitude and the cause for the signal-to-noise ratio change, in addition to the signal-to-noise ratio, remedies the detection and tracking of tonals that appear/disappear relative to the background. The additional use of tonal width is suggested as a means to remedy the problem of crossed tonals.


2021 ◽  
pp. 113372
Author(s):  
Tomasz Tokarski ◽  
Gert Nolze ◽  
Aimo Winkelmann ◽  
Łukasz Rychłowski ◽  
Piotr Bała ◽  
...  

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