Multi-channel acoustic analysis of phoneme /s/ mispronunciation for lateral sigmatism detection

Krecichwost, Michal; Miodońska, Zuzanna; Badura, Paweł; Trzaskalik, Joanna; Moćko, Natalia

doi:10.1016/j.bbe.2018.11.005

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…Martijn Wieling and Tobias Cincarek et al built an NDL-based automatic oral English evaluation model based on simple discriminative learning (NDL) oral English pronunciation distance [3,4]. Wiehan Agenbag, Michal Krecichwost, and others proposed a method of unsupervised discovering subword units (SWU) and related pronunciation dictionaries for automatic speech recognition (ASR) systems, and realized automatic evaluation of spoken english by iterative reduction of pronunciation variation using Inter-word aggregation and model pruning [5,6]. Savchenko and Daniel Felps et al, by examining the gain optimization of the spectral distortion measure between oral English learners and calculating the sound generated by learners, proposed to use the gradient descent optimization of gain difference optimization to adapt to the linear prediction coding coefficient of the reference sound, and realized the automatic evaluation of oral English and the training of oral English pronunciation [7,8].…”

Section: Forewordmentioning

confidence: 99%

Automatic Evaluation Method of Oral English Based on Multiplex Mode

Chi

2022

Wireless Communications and Mobile Computing

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For the problem of the low accuracy of large-scale oral English, based on oral English from the perspective of difficulty of oral English text and phonology, a multimodal-based automatic oral English assessment method is proposed by using L2 regularized (multilayer perceptron, MLP) and 9 features affecting the automated assessment of oral English as model input. Simulation results show that the proposed method can well predictively assess oral English difficulty and performs well on RMSE and R2 metrics of 0.053 and 0.905, respectively, with certain advantages over conventional elastic network-based and random forest-based prediction models.

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Section: Forewordmentioning

confidence: 99%

Automatic Evaluation Method of Oral English Based on Multiplex Mode

Chi

2022

Wireless Communications and Mobile Computing

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“…Data acquisition systems described in literature feature specific drawbacks that limit their usefulness for the considered problem. Based on the analysis of these systems and our previous preliminary studies [26], [27], we have formulated a set of assumptions that should be met by an applicable measurement method.…”

Section: B Aims and Scopementioning

confidence: 99%

Multichannel Speech Acquisition and Analysis for Computer-Aided Sigmatism Diagnosis in Children

et al. 2020

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A novel concept for acoustic data acquisition for computer-aided diagnosis of a common speech disorder (sigmatism) is presented in this paper. We designed and built a data acquisition device enabling repeatable speech signal acquisition in up to fifteen spatially-organized acoustic channels. The system is safe, non-invasive, comfortable, visually attractive to the user, and does not affect the articulation process. It is easy and convenient to use and transport and does not require a specialized measuring room. We collected a large speech corpus containing speech samples from 107 children aged five or six. The data were acquired according to a dedicated protocol. They consisted of multichannel acoustic recordings of selected words containing sibilants and diagnostic descriptions of articulatory features prepared by speech therapy experts. The data acquisition device was examined for responses and repeatability of individual microphones in the presence of various synthetic and human-generated acoustic stimuli. Then, it was verified for its ability to indicate distinctive patterns in spatial energy distribution in different realizations of two sibilants: /s/, /S/ in three pronunciation categories each, based on collected speech-articulation corpus. The results confirm that a multichannel speech signal can be successfully employed for the analysis of the spatial distribution of airflow during normative or pathological realization of sibilant sounds in children. The method is promising for comprehensive analysis of articulatory features, which follows new trends in the description of speech disorders; such an approach was not employed in speech diagnosis or therapy so far.

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“…In recent studies (Krecichwost, et al, 2019; 2020) a microphone arrays are used in multichannel acquisition devices for computer-aided diagnostics of speech disorders. A specially designed head-worn acoustic mask with spatially arranged microphones located in front of subject's mouth enables recording of the speech signal with increased signal-to-noise ratio of the weak speech components.…”

Section: Introductionmentioning

confidence: 99%

Archives of Acoustics

Šarić,

Subotić,

Bilibajkić

et al. 2021

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Microphone array with minimum variance (MVDR) beamformer is a commonly used method for ambient noise suppression. Unfortunately, the performance of the MVDR beamformer is poor in a real reverberant room due to multipath wave propagation. To overcome this problem, we propose three improvements. Firstly, we propose end-fire microphone array that has been shown to have a better directivity index than the corresponding broadside microphone array. Secondly, we propose the use of unidirectional microphones instead of omnidirectional ones. Thirdly, we propose an adaptation of its adaptive algorithm during the pause of speech, which improves its robustness against the room reverberation and deviation from the optimal receiving direction. The performance of the proposed microphone array was theoretically analyzed using a diffuse noise model. Simulation analysis was performed for combined diffuse and coherent noise using the image model of the reverberant room. Real room tests were conducted using a four-microphone array placed in a small office room. The theoretical analysis and the real room tests showed that the proposed solution considerably improves speech quality.

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Multi-channel acoustic analysis of phoneme /s/ mispronunciation for lateral sigmatism detection

Cited by 9 publications

References 15 publications

Automatic Evaluation Method of Oral English Based on Multiplex Mode

Automatic Evaluation Method of Oral English Based on Multiplex Mode

Multichannel Speech Acquisition and Analysis for Computer-Aided Sigmatism Diagnosis in Children

Archives of Acoustics

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