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Potential of automatic speech processing technologies for early detection of oral language disorders: a meta-analytic review ...
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РЕЧЕВЕДЕНИЕ: ИСТОРИЯ, ТЕОРИЯ, ПРАКТИКА ... : SPEECHSCIENCE: HISTORY, THEORY, PRACTICE ...
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Соловьева Наталья Васильевна. - : Вестник Пермского государственного гуманитарно-педагогического университета. Серия № 3. Гуманитарные и общественные науки, 2022
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“Thou Shalt Not Take the Lord’s Name in Vain”: A Methodological Proposal to Identify Religious Hate Content on Digital Social Networks
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In: International Journal of Communication; Vol 16 (2022); 22 ; 1932-8036 (2022)
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Об истории речевых исследований в России ... : About the history of speech research in Russia ...
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The Impact of George W. Bush's Political Discourses on the Invasion of Iraq: A Corpus-Based Rhetoric Discourse Analysis ...
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The Impact of George W. Bush's Political Discourses on the Invasion of Iraq: A Corpus-Based Rhetoric Discourse Analysis ...
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Does high talker variability improve the learning of non-native phoneme contrasts? A replication ...
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A Preliminary Report of Network Electroencephalographic Measures in Primary Progressive Apraxia of Speech and Aphasia
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In: Brain Sciences; Volume 12; Issue 3; Pages: 378 (2022)
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Differences and Commonalities in Children with Childhood Apraxia of Speech and Comorbid Neurodevelopmental Disorders: A Multidimensional Perspective
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In: Journal of Personalized Medicine; Volume 12; Issue 2; Pages: 313 (2022)
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Contribution of Vocal Tract and Glottal Source Spectral Cues in the Generation of Acted Happy and Aggressive Spanish Vowels
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In: Applied Sciences; Volume 12; Issue 4; Pages: 2055 (2022)
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A Rule-Based Grapheme-to-Phoneme Conversion System
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2758 (2022)
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Many Changes in Speech through Aging Are Actually a Consequence of Cognitive Changes
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 4; Pages: 2137 (2022)
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Artificial Neural Networks Combined with the Principal Component Analysis for Non-Fluent Speech Recognition
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In: Sensors; Volume 22; Issue 1; Pages: 321 (2022)
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Abstract:
The presented paper introduces principal component analysis application for dimensionality reduction of variables describing speech signal and applicability of obtained results for the disturbed and fluent speech recognition process. A set of fluent speech signals and three speech disturbances—blocks before words starting with plosives, syllable repetitions, and sound-initial prolongations—was transformed using principal component analysis. The result was a model containing four principal components describing analysed utterances. Distances between standardised original variables and elements of the observation matrix in a new system of coordinates were calculated and then applied in the recognition process. As a classifying algorithm, the multilayer perceptron network was used. Achieved results were compared with outcomes from previous experiments where speech samples were parameterised with the Kohonen network application. The classifying network achieved overall accuracy at 76% (from 50% to 91%, depending on the dysfluency type).
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Keyword:
artificial neural networks; principal component analysis; speech recognition; stuttering
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URL: https://doi.org/10.3390/s22010321
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Data-Driven Analysis of European Portuguese Nasal Vowel Dynamics in Bilabial Contexts
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4601 (2022)
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Rethinking the Methods and Algorithms for Inner Speech Decoding and Making Them Reproducible
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In: NeuroSci; Volume 3; Issue 2; Pages: 226-244 (2022)
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Using acoustic distance and acoustic absement to quantify lexical competition
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DCT vs. corpus orales: reflexiones metodológicas sobre el estudio de los actos de habla ; DCT vs. spoken corpora: methodologic reflections on the study of speech acts
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In: Pragmalingüística, (29), 377-395 (2022)
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Психофизиологические механизмы, лежащие в основе процесса восприятия речи ; Psychophysiological Mechanisms of the Speech Perception Process
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Квантитативный анализ речевого наполнения англоязычных телесериалов ; Quantitative Analysis of Speech Content of English-Language Television Series
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