9786204738581 - detection of sigmatism with the aid of machine learning: for german speakers di barabashova, kristina (5 risultati)
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Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,05
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: 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]prei…gu[dot]de | Anbieter: preigu.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: 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.
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Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 32,02
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: 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 goo…d, making the life of people mor.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 crea…te 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 %.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 38,12
EUR 60,69 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: 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 creat…e 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 %.
