Time-frequency representations in speech perception

Gómez-Vilda, Pedro; Vicente, José Manuel Ferrández; Rodellar, V.; Fernández-Baíllo, Roberto

doi:10.1016/j.neucom.2008.04.056

Cited by 13 publications

(5 citation statements)

References 19 publications

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“…The 2.5 kHz threshold has a tentative physiological justification: most of the energy in the sustained vowels is contained mainly up to the second formant, and for the sustained vowel /a/ the second formant can be up to about 1.7 kHz [8]. Interestingly, another research group has reported that frequencies above 2 kHz can be generally considered turbulent noise [30]. Similarly, the Multi-Dimensional Voice Program (MDVP) uses a dysphonia measure called "Voice Turbulence Index," where the spectral frequencies above 2.8 kHz are used to quantify the high frequency energy component in the speech signal [31].…”

Section: A Feature Calculationmentioning

confidence: 99%

Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

Tsanas

Little

Fox

et al. 2014

IEEE Trans. Neural Syst. Rehabil. Eng.

193

111

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Vocal performance degradation is a common symptom for the vast majority of Parkinson's disease (PD) subjects, who typically follow personalized one-to-one periodic rehabilitation meetings with speech experts over a long-term period. Recently, a novel computer program called Lee Silverman voice treatment (LSVT) Companion was developed to allow PD subjects to independently progress through a rehabilitative treatment session. This study is part of the assessment of the LSVT Companion, aiming to investigate the potential of using sustained vowel phonations towards objectively and automatically replicating the speech experts' assessments of PD subjects' voices as "acceptable" (a clinician would allow persisting during in-person rehabilitation treatment) or "unacceptable" (a clinician would not allow persisting during in-person rehabilitation treatment). We characterize each of the 156 sustained vowel /a/ phonations with 309 dysphonia measures, select a parsimonious subset using a robust feature selection algorithm, and automatically distinguish the two cohorts (acceptable versus unacceptable) with about 90% overall accuracy. Moreover, we illustrate the potential of the proposed methodology as a probabilistic decision support tool to speech experts to assess a phonation as "acceptable" or "unacceptable." We envisage the findings of this study being a first step towards improving the effectiveness of an automated rehabilitative speech assessment tool.

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Section: A Feature Calculationmentioning

confidence: 99%

Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

Tsanas

Little

Fox

et al. 2014

IEEE Trans. Neural Syst. Rehabil. Eng.

193

111

View full text Add to dashboard Cite

show abstract

“…Interestingly, broadly similar findings regarding the threshold of ‘signal’ and ‘noise’ have been described by other research groups. For example, Gomez-Vilda et al [63] indicated that frequencies above 2 kHz can be generally considered turbulent noise. Likewise, the Multi-Dimensional Voice Program (MDVP - ) program includes “Voice Turbulence Index”, which is an alternative dysphonia measure relying on the SNR concept, where the spectral energy above 2.8 kHz is used to denote the high frequency energy component in the speech signal [64] .…”

Section: Discussionmentioning

confidence: 99%

Remote Assessment of Parkinson’s Disease Symptom Severity Using the Simulated Cellular Mobile Telephone Network

2021

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“…The bioinspired model implemented is shown in Figure 1. The first two blocks correspond with the proposal described in [7][8][9]. The last block corresponds with the bioinspired model presented by the authors for vowel recognition as one of the functions of the higher auditory system using an artificial neural network (ANN).…”

Section: Methodsmentioning

confidence: 99%

“…In recent years, several auditory models almost entirely capable of reproducing the functioning of human biological systems have been proposed. A few authors, among which are [7][8][9][10][11][12][13][14][15][16][17], propose models that reproduce in an equivalent way the behavior of the structures involved in the analysis of the voice. These designs constitute bioinspired models capable of understanding and imitating the biological responses of the auditory system.…”

Section: Introductionmentioning

confidence: 99%

Bioinspired Auditory Model for Vowel Recognition

2021

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In this work, a bioinspired or neuromorphic model to replicate the vowel recognition process for an auditory system is presented. A bioinspired peripheral and central auditory system model is implemented and a neuromorphic higher auditory system model based on artificial neuronal nets for vowel recognition is proposed. For their verification, ten Hispanic Spanish language-speaking adults (five males and five females) were used. With the proposed bioinspired model based on artificial neuronal nets it is possible to recognize with high levels of accuracy and sensibility the vowels phonemes of speech signals and the assessment of cochlear implant stimulation strategies in terms of vowel recognition.

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Time-frequency representations in speech perception

Cited by 13 publications

References 19 publications

Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

Remote Assessment of Parkinson’s Disease Symptom Severity Using the Simulated Cellular Mobile Telephone Network

Bioinspired Auditory Model for Vowel Recognition

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