Reading and speech intelligibility of a child with auditory impairment and cochlear implant.

2018 ◽  
Vol 11 (3) ◽  
pp. 306-316 ◽  
Author(s):  
Fernando Del Mando Lucchesi ◽  
Ana Claudia Moreira Almeida-Verdu ◽  
Deisy das Graças de Souza
2020 ◽  
Author(s):  
Lieber Po-Hung Li ◽  
Ji-Yan Han ◽  
Wei-Zhong Zheng ◽  
Ren-Jie Huang ◽  
Ying-Hui Lai

BACKGROUND The cochlear implant technology is a well-known approach to help deaf patients hear speech again. It can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction (NR), such as noise classification and deep denoising autoencoder (NC+DDAE), can benefit the intelligibility performance of patients with cochlear implants compared to classical noise reduction algorithms. OBJECTIVE Following the successful implementation of the NC+DDAE model in our previous study, this study aimed to (1) propose an advanced noise reduction system using knowledge transfer technology, called NC+DDAE_T, (2) examine the proposed NC+DDAE_T noise reduction system using objective evaluations and subjective listening tests, and (3) investigate which layer substitution of the knowledge transfer technology in the NC+DDAE_T noise reduction system provides the best outcome. METHODS The knowledge transfer technology was adopted to reduce the number of parameters of the NC+DDAE_T compared with the NC+DDAE. We investigated which layer should be substituted using short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) scores, as well as t-distributed stochastic neighbor embedding to visualize the features in each model layer. Moreover, we enrolled ten cochlear implant users for listening tests to evaluate the benefits of the newly developed NC+DDAE_T. RESULTS The experimental results showed that substituting the middle layer (ie, the second layer in this study) of the noise-independent DDAE (NI-DDAE) model achieved the best performance gain regarding STOI and PESQ scores. Therefore, the parameters of layer three in the NI-DDAE were chosen to be replaced, thereby establishing the NC+DDAE_T. Both objective and listening test results showed that the proposed NC+DDAE_T noise reduction system achieved similar performances compared with the previous NC+DDAE in several noisy test conditions. However, the proposed NC+DDAE_T only needs a quarter of the number of parameters compared to the NC+DDAE. CONCLUSIONS This study demonstrated that knowledge transfer technology can help to reduce the number of parameters in an NC+DDAE while keeping similar performance rates. This suggests that the proposed NC+DDAE_T model may reduce the implementation costs of this noise reduction system and provide more benefits for cochlear implant users.


2010 ◽  
Vol 10 ◽  
pp. 329-339 ◽  
Author(s):  
Torsten Rahne ◽  
Michael Ziese ◽  
Dorothea Rostalski ◽  
Roland Mühler

This paper describes a logatome discrimination test for the assessment of speech perception in cochlear implant users (CI users), based on a multilingual speech database, the Oldenburg Logatome Corpus, which was originally recorded for the comparison of human and automated speech recognition. The logatome discrimination task is based on the presentation of 100 logatome pairs (i.e., nonsense syllables) with balanced representations of alternating “vowel-replacement” and “consonant-replacement” paradigms in order to assess phoneme confusions. Thirteen adult normal hearing listeners and eight adult CI users, including both good and poor performers, were included in the study and completed the test after their speech intelligibility abilities were evaluated with an established sentence test in noise. Furthermore, the discrimination abilities were measured electrophysiologically by recording the mismatch negativity (MMN) as a component of auditory event-related potentials. The results show a clear MMN response only for normal hearing listeners and CI users with good performance, correlating with their logatome discrimination abilities. Higher discrimination scores for vowel-replacement paradigms than for the consonant-replacement paradigms were found. We conclude that the logatome discrimination test is well suited to monitor the speech perception skills of CI users. Due to the large number of available spoken logatome items, the Oldenburg Logatome Corpus appears to provide a useful and powerful basis for further development of speech perception tests for CI users.


2013 ◽  
Vol 56 (4) ◽  
pp. 1075-1084 ◽  
Author(s):  
Carina Pals ◽  
Anastasios Sarampalis ◽  
Deniz Başkent

Purpose Fitting a cochlear implant (CI) for optimal speech perception does not necessarily optimize listening effort. This study aimed to show that listening effort may change between CI processing conditions for which speech intelligibility remains constant. Method Nineteen normal-hearing participants listened to CI simulations with varying numbers of spectral channels. A dual-task paradigm combining an intelligibility task with either a linguistic or nonlinguistic visual response-time (RT) task measured intelligibility and listening effort. The simultaneously performed tasks compete for limited cognitive resources; changes in effort associated with the intelligibility task are reflected in changes in RT on the visual task. A separate self-report scale provided a subjective measure of listening effort. Results All measures showed significant improvements with increasing spectral resolution up to 6 channels. However, only the RT measure of listening effort continued improving up to 8 channels. The effects were stronger for RTs recorded during listening than for RTs recorded between listening. Conclusion The results suggest that listening effort decreases with increased spectral resolution. Moreover, these improvements are best reflected in objective measures of listening effort, such as RTs on a secondary task, rather than intelligibility scores or subjective effort measures.


2020 ◽  
Vol 24 ◽  
pp. 233121652097034
Author(s):  
Florian Langner ◽  
Andreas Büchner ◽  
Waldo Nogueira

Cochlear implant (CI) sound processing typically uses a front-end automatic gain control (AGC), reducing the acoustic dynamic range (DR) to control the output level and protect the signal processing against large amplitude changes. It can also introduce distortions into the signal and does not allow a direct mapping between acoustic input and electric output. For speech in noise, a reduction in DR can result in lower speech intelligibility due to compressed modulations of speech. This study proposes to implement a CI signal processing scheme consisting of a full acoustic DR with adaptive properties to improve the signal-to-noise ratio and overall speech intelligibility. Measurements based on the Short-Time Objective Intelligibility measure and an electrodogram analysis, as well as behavioral tests in up to 10 CI users, were used to compare performance with a single-channel, dual-loop, front-end AGC and with an adaptive back-end multiband dynamic compensation system (Voice Guard [VG]). Speech intelligibility in quiet and at a +10 dB signal-to-noise ratio was assessed with the Hochmair–Schulz–Moser sentence test. A logatome discrimination task with different consonants was performed in quiet. Speech intelligibility was significantly higher in quiet for VG than for AGC, but intelligibility was similar in noise. Participants obtained significantly better scores with VG than AGC in the logatome discrimination task. The objective measurements predicted significantly better performance estimates for VG. Overall, a dynamic compensation system can outperform a single-stage compression (AGC + linear compression) for speech perception in quiet.


2019 ◽  
Author(s):  
Mark D. Fletcher ◽  
Amatullah Hadeedi ◽  
Tobias Goehring ◽  
Sean R Mills

Cochlear implant (CI) users receive only limited sound information through their implant, which means that they struggle to understand speech in noisy environments. Recent work has suggested that combining the electrical signal from the CI with a haptic signal that provides crucial missing sound information (“electro-haptic stimulation”; EHS) could improve speech-in-noise performance. The aim of the current study was to test whether EHS could enhance speech-in-noise performance in CI users using: (1) a tactile signal derived using an algorithm that could be applied in real time, (2) a stimulation site appropriate for a real-world application, and (3) a tactile signal that could readily be produced by a compact, portable device. We measured speech intelligibility in multi-talker noise with and without vibro-tactile stimulation of the wrist in CI users, before and after a short training regime. No effect of EHS was found before training, but after training EHS was found to improve the number of words correctly identified by an average of 8.3 %-points, with some users improving by more than 20 %-points. Our approach could offer an inexpensive and non-invasive means of improving speech-in-noise performance in CI users.


Author(s):  
Siriporn Dachasilaruk ◽  
Niphat Jantharamin ◽  
Apichai Rungruang

Cochlear implant (CI) listeners encounter difficulties in communicating with other persons in noisy listening environments. However, most CI research has been carried out using the English language. In this study, single-channel speech enhancement (SE) strategies as a pre-processing approach for the CI system were investigated in terms of Thai speech intelligibility improvement. Two SE algorithms, namely multi-band spectral subtraction (MBSS) and Weiner filter (WF) algorithms, were evaluated. Speech signals consisting of monosyllabic and bisyllabic Thai words were degraded by speech-shaped noise and babble noise at SNR levels of 0, 5, and 10 dB. Then the noisy words were enhanced using SE algorithms. The enhanced words were fed into the CI system to synthesize vocoded speech. The vocoded speech was presented to twenty normal-hearing listeners. The results indicated that speech intelligibility was marginally improved by the MBSS algorithm and significantly improved by the WF algorithm in some conditions. The enhanced bisyllabic words showed a noticeably higher intelligibility improvement than the enhanced monosyllabic words in all conditions, particularly in speech-shaped noise. Such outcomes may be beneficial to Thai-speaking CI listeners.


2015 ◽  
Vol 36 (7) ◽  
pp. 1197-1202 ◽  
Author(s):  
Wilhelm Wimmer ◽  
Marco Caversaccio ◽  
Martin Kompis

2018 ◽  
Vol 23 (1) ◽  
pp. 32-38 ◽  
Author(s):  
Jantien L. Vroegop ◽  
Nienke C. Homans ◽  
André Goedegebure ◽  
J. Gertjan Dingemanse ◽  
Teun van Immerzeel ◽  
...  

Although the benefit of bimodal listening in cochlear implant users has been agreed on, speech comprehension remains a challenge in acoustically complex real-life environments due to reverberation and disturbing background noises. One way to additionally improve bimodal auditory performance is the use of directional microphones. The objective of this study was to investigate the effect of a binaural beamformer for bimodal cochlear implant (CI) users. This prospective study measured speech reception thresholds (SRT) in noise in a repeated-measures design that varied in listening modality for static and dynamic listening conditions. A significant improvement in SRT of 4.7 dB was found with the binaural beamformer switched on in the bimodal static listening condition. No significant improvement was found in the dynamic listening condition. We conclude that there is a clear additional advantage of the binaural beamformer in bimodal CI users for predictable/static listening conditions with frontal target speech and spatially separated noise sources.


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