Inhaltsangabe
The book is devoted to automatic detection of sigmatism in adult speech of German speakers. It has two major purposes: (1) to find an optimal set of audio features providing distinction between normal and disordered speech; (2) to create a Machine Learning (ML) classification algorithm able to analyze extracted features and detect sigmatism at phone level. The features are selected according to the phonetic background of considered sounds.They include first three formants, root-mean-square (RMS) amplitude, spectral peaks, spectral centroid, spectral skewness, and first 12 mel-frequency cepstral coefficients (MFCCs). Three ML methods are considered for sigmatism detection: Support Vector Machine, Gaussian Process, and Neural Networks. The process of feature extraction as well as automatic classification are conducted via Python scripts. As a result, the model based on SVM with the RBF kernel showed the highest accuracy rate of 90.6 %.
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Über die Autorin bzw. den Autor
O meu nome é Kristina. Estou estudando e trabalhando na área de tecnologias da fala e da linguagem. Meu objetivo pessoal é adquirir habilidades e conhecimentos que eu possa usar para o bem público, tornando a vida das pessoas mais confortável e segura com a ajuda de métodos e ferramentas de inteligência artificial (IA).
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Detection of Sigmatism with the aid of Machine Learning
Verlag:
LAP LAMBERT Academic Publishing Jan 2022, 2022
ISBN 10: 6204738585
ISBN 13: 9786204738581
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is devoted to automatic detection of sigmatism in adult speech of German speakers. It has two major purposes: (1) to find an optimal set of audio features providing distinction between normal and disordered speech; (2) to create a Machine Learning (ML) classification algorithm able to analyze extracted features and detect sigmatism at phone level. The features are selected according to the phonetic background of considered sounds.They include first three formants, root-mean-square (RMS) amplitude, spectral peaks, spectral centroid, spectral skewness, and first 12 mel-frequency cepstral coefficients (MFCCs). Three ML methods are considered for sigmatism detection: Support Vector Machine, Gaussian Process, and Neural Networks. The process of feature extraction as well as automatic classification are conducted via Python scripts. As a result, the model based on SVM with the RBF kernel showed the highest accuracy rate of 90.6 %. 80 pp. Englisch. Bestandsnummer des Verkäufers 9786204738581
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Detection of Sigmatism with the aid of Machine Learning
Verlag:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204738585
ISBN 13: 9786204738581
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Barabashova KristinaMy name is Kristina. I am studying and working in the area of speech and language technologies. My personal goal is to acquire skills and knowledge that I can use for the public good, making the life of people mor. Bestandsnummer des Verkäufers 560259895
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Detection of Sigmatism with the aid of Machine Learning
Verlag:
LAP LAMBERT Academic Publishing Jan 2022, 2022
ISBN 10: 6204738585
ISBN 13: 9786204738581
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -The book is devoted to automatic detection of sigmatism in adult speech of German speakers. It has two major purposes: (1) to find an optimal set of audio features providing distinction between normal and disordered speech; (2) to create a Machine Learning (ML) classification algorithm able to analyze extracted features and detect sigmatism at phone level. The features are selected according to the phonetic background of considered sounds.They include first three formants, root-mean-square (RMS) amplitude, spectral peaks, spectral centroid, spectral skewness, and first 12 mel-frequency cepstral coefficients (MFCCs). Three ML methods are considered for sigmatism detection: Support Vector Machine, Gaussian Process, and Neural Networks. The process of feature extraction as well as automatic classification are conducted via Python scripts. As a result, the model based on SVM with the RBF kernel showed the highest accuracy rate of 90.6 %.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch. Bestandsnummer des Verkäufers 9786204738581
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Detection of Sigmatism with the aid of Machine Learning : for German Speakers
Verlag:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204738585
ISBN 13: 9786204738581
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book is devoted to automatic detection of sigmatism in adult speech of German speakers. It has two major purposes: (1) to find an optimal set of audio features providing distinction between normal and disordered speech; (2) to create a Machine Learning (ML) classification algorithm able to analyze extracted features and detect sigmatism at phone level. The features are selected according to the phonetic background of considered sounds.They include first three formants, root-mean-square (RMS) amplitude, spectral peaks, spectral centroid, spectral skewness, and first 12 mel-frequency cepstral coefficients (MFCCs). Three ML methods are considered for sigmatism detection: Support Vector Machine, Gaussian Process, and Neural Networks. The process of feature extraction as well as automatic classification are conducted via Python scripts. As a result, the model based on SVM with the RBF kernel showed the highest accuracy rate of 90.6 %. Bestandsnummer des Verkäufers 9786204738581
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Detection of Sigmatism with the aid of Machine Learning | for German Speakers
Verlag:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204738585
ISBN 13: 9786204738581
Neu
Taschenbuch
Anbieter: preigu, Osnabrück, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Detection of Sigmatism with the aid of Machine Learning | for German Speakers | Kristina Barabashova | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204738581 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 121163731
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