Changes of Dynamic Range, Signal-to-Noise Ratio, and Consonant-to-Vowel Ratio by Electroacoustic Adjustment and Fitting in Non-linear Hearing Aids

2014 ◽  
Vol 10 (3) ◽  
pp. 190-197 ◽  
Author(s):  
Kyoung Won Lee
Keyword(s):  
Hearing Aids ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Non Linear ◽  
Noise Ratio ◽  
Fitting In

scholarly journals Signal-to-Noise-Ratio-Aware Dynamic Range Compression in Hearing Aids

2018 ◽  
Vol 22 ◽  
pp. 233121651879090 ◽  
Author(s):  
Tobias May ◽  
Borys Kowalewski ◽  
Torsten Dau
Keyword(s):  
Hearing Aids ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Dynamic Range Compression ◽  
Noise Ratio

scholarly journals Perceptual Evaluation of Signal-to-Noise-Ratio-Aware Dynamic Range Compression in Hearing Aids

2020 ◽  
Vol 24 ◽  
pp. 233121652093053
Author(s):  
Borys Kowalewski ◽  
Torsten Dau ◽  
Tobias May
Keyword(s):  
Hearing Aids ◽  
Speech Intelligibility ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Perceptual Evaluation ◽  
Dynamic Range Compression ◽  
Subjective Preference ◽  
Noise Ratio ◽  
Fast Acting

Dynamic range compression is a compensation strategy commonly used in modern hearing aids. Fast-acting systems respond relatively quickly to the fluctuations in the input level. This allows for more effective compression of the dynamic range of speech and hence enhanced the audibility of its low-intensity components. However, such processing also amplifies the background noise, distorts the modulation spectra of both the speech and the background, and can reduce the output signal-to-noise ratio (SNR). Recently, May et al. proposed a novel SNR-aware compression strategy, in which the compression speed is adapted depending on whether speech is present or absent. Fast-acting compression is applied to speech-dominated time–frequency (T-F) units, while noise-dominated T-F units are processed using slow-acting compression. It has been shown that this strategy provides a similar effective compression of the speech dynamic range as conventional fast-acting compression, while introducing fewer distortions of the modulation spectrum of the background and providing an improved output SNR. In this study, this SNR-aware compression strategy was compared with conventional fast- and slow-acting compression in terms of speech intelligibility and subjective preference in a group of 17 hearing-impaired listeners with varying degree of hearing loss. The results show a speech intelligibility benefit of the SNR-aware compression strategy over the conventional slow-acting system. Furthermore, the SNR-aware approach demonstrates an increased subjective preference compared with both conventional fast- and slow-acting systems.

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

2020 ◽  
Vol 2020 (7) ◽  
pp. 143-1-143-6 ◽  
Author(s):  
Yasuyuki Fujihara ◽  
Maasa Murata ◽  
Shota Nakayama ◽  
Rihito Kuroda ◽  
Shigetoshi Sugawa
Keyword(s):  
Linear Response ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Signal To Noise ◽  
Single Exposure ◽  
Two Stage ◽  
Noise Ratio ◽  
Maximum Signal

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

scholarly journals Estimation and Correction of Sampling Time Offsets in Tiadcs using Optimization Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1217-1222
Keyword(s):  
Optimization Algorithm ◽  
High Frequency ◽  
Performance Metrics ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Sampling Time ◽  
Signal To Noise ◽  
High Sampling ◽  
Noise Ratio ◽  
Estimation And Correction

In recent communication technologies, very high sampling rates are required for rf signals particularly for signals coming under ultra high frequency (UHF), super high frequency (SHF) and extremely high frequency (EHF) ranges. The applications include global positioning system (GPS), satellite communication, radar, radio astronomy, 5G mobile phones etc. Such high sampling rates can be accomplished with time-interleaved analog to digital converters (TIADCs). However, sampling time offsets existing in TIADCs produce non-uniform samples. This poses a drawback in the reconstruction of the signal. The current paper addresses this drawback and offers a solution for improved signal reconstruction by estimation and correction of the offsets. A modified differential evolution (MDE) algorithm, which is an optimization algorithm, is used for estimating the sampling time offsets and the estimated offsets are used for correction. The estimation algorithm is implemented on an FPGA board and correction is implemented using MATLAB. The power consumption of FPGA for implementation is 57mW. IO utilization is 27% for 4-channel TIADCs and 13% for 2-channel TIADCs. The algorithm estimated the sampling time offsets precisely. For estimation the algorithm uses a sinusoidal signal as a test signal. Correction is performed with sinusoidal and speech signals as inputs for TIADCs. Performance metrics used for evaluating the algorithm are SNR (signal to noise ratio), SNDR (signal to noise and distortion ratio), SFDR (spurious-free dynamic range) and PSNR (peak signal to noise ratio). A noteworthy improvement is observed in the above mentioned parameters. Results are compared with the existing state of the art algorithms and superiority of the proposed algorithm is verified.

Non-linear filtering of rare events with large signal-to-noise ratio

1987 ◽  
Vol 24 (04) ◽  
pp. 929-948
Author(s):  
A. J. Heunis
Keyword(s):  
Conditional Distribution ◽  
Signal To Noise Ratio ◽  
Sample Path ◽  
Rare Event ◽  
Dirac Measure ◽  
Linear Filtering ◽  
Large Signal ◽  
Signal To Noise ◽  
Non Linear ◽  
Noise Ratio

The theory of robust non-linear filtering in Clark (1978) and Davis (1980), (1982) is used to evaluate the limiting conditional distribution of a diffusion, given an observation of a ‘rare-event' sample-path of the diffusion, as the signal-to-noise ratio and the diffusion noise-intensity converge to infinity and zero respectively. Under mild conditions it is shown that the limiting conditional distribution is a Dirac measure concentrated at a trajectory which solves a variational problem parametrised by the sample-path of the observed signal.

scholarly journals Consistency of Hearing Aid Setting Preference in Simulated Real-World Environments: Implications for Trainable Hearing Aids

2020 ◽  
Vol 24 ◽  
pp. 233121652093339
Author(s):  
Els Walravens ◽  
Gitte Keidser ◽  
Louise Hickson
Keyword(s):  
Hearing Aids ◽  
Real World ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Traffic Noise ◽  
Fine Tuning ◽  
Signal To Noise ◽  
Acoustic Environment ◽  
Change Environment ◽  
Noise Ratio

Trainable hearing aids let users fine-tune their hearing aid settings in their own listening environment: Based on consistent user-adjustments and information about the acoustic environment, the trainable aids will change environment-specific settings to the user’s preference. A requirement for effective fine-tuning is consistency of preference for similar settings in similar environments. The aim of this study was to evaluate consistency of preference for settings differing in intensity, gain-frequency slope, and directionality when listening in simulated real-world environments and to determine if participants with more consistent preferences could be identified based on profile measures. A total of 52 adults (63–88 years) with hearing varying from normal to a moderate sensorineural hearing loss selected their preferred setting from pairs differing in intensity (3 or 6 dB), gain-frequency slope (±1.3 or ± 2.7 dB/octave), or directionality (omnidirectional vs. cardioid) in four simulated real-world environments: traffic noise, a monologue in traffic noise at 5 dB signal-to-noise ratio, and a dialogue in café noise at 5 and at 0 dB signal-to-noise ratio. Forced-choice comparisons were made 10 times for each combination of pairs of settings and environment. Participants also completed nine psychoacoustic, cognitive, and personality measures. Consistency of preference, defined by a setting preferred at least 9 out of 10 times, varied across participants. More participants obtained consistent preferences for larger differences between settings and less difficult environments. The profile measures did not predict consistency of preference. Trainable aid users could benefit from counselling to ensure realistic expectations for particular adjustments and listening situations.

Effects of Adaptive Hearing Aid Directionality and Noise Reduction on Masked Speech Recognition for Children Who Are Hard of Hearing

2019 ◽  
Vol 28 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Jenna M. Browning ◽  
Emily Buss ◽  
Mary Flaherty ◽  
Tim Vallier ◽  
Lori J. Leibold
Keyword(s):  
Speech Recognition ◽  
Hearing Aids ◽  
Hard Of Hearing ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Normal Hearing ◽  
Signal To Noise ◽  
Open Set ◽  
Fully Adaptive ◽  
Noise Ratio

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.

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