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標題: Titlebook: Robust Emotion Recognition using Spectral and Prosodic Features; K. Sreenivasa Rao,Shashidhar G. Koolagudi Book 2013 The Author(s) 2013 Sp [打印本頁]

作者: Malicious    時間: 2025-3-21 18:57
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書目名稱Robust Emotion Recognition using Spectral and Prosodic Features被引頻次




書目名稱Robust Emotion Recognition using Spectral and Prosodic Features被引頻次學科排名




書目名稱Robust Emotion Recognition using Spectral and Prosodic Features年度引用




書目名稱Robust Emotion Recognition using Spectral and Prosodic Features年度引用學科排名




書目名稱Robust Emotion Recognition using Spectral and Prosodic Features讀者反饋




書目名稱Robust Emotion Recognition using Spectral and Prosodic Features讀者反饋學科排名





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K. Sreenivasa Rao,Shashidhar G. Koolagudien aus Praxis und Wissenschaft liefern Grund- und Fachwissen.Hervorragende Fachautoren beschreiben ihre Erfahrungen zu Tragwerkstypen, Berechnungs-, Herstellungs- und Bauausführungsverfahren sowie Bauüberwachungsmethoden. Gegenüber den beiden vorangegangenen Auflagen wird im Einführungskapitel auf d
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K. Sreenivasa Rao,Shashidhar G. Koolagudigsmethoden. Gegenüber den beiden vorangegangenen Auflagen wird im Einführungskapitel auf die neuere Entwicklung der Verwendung von Hochleistungsbeton im Brückenbau sowie auf Brücken aus Textilbeton eingegangen. Des Weiteren werden in diesem Kapitel integrale und semiintegrale Brücken behandelt, es w
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K. Sreenivasa Rao,Shashidhar G. KoolagudiDeals with emotions in terms of how to characterize the emotions, how to acquire the emotion-specific information from speech conversations and finally how to incorporate the acquired emotion-specific
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Book 2013d syllable levels in different parts of the utterance) features for discerning emotions in a robust manner.The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. F
作者: electrolyte    時間: 2025-3-24 08:02
Robust Emotion Recognition using Speaking Rate Features,cond stage emotions in each broad group are further classified. Spectral and prosodic features are explored in each stage for discriminating the emotions. Combination of spectral and prosodic features is observed to be performed better.
作者: surrogate    時間: 2025-3-24 12:38
Book 2013eatures based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.
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Introduction,speech emotion recognition are mentioned. Important state-of-the-art issues prevailing in the area of emotional speech processing are discussed at the end of the chapter along with a note on the organization of the book.
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Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features,ng in nature. By properly exploiting these evidences, the recognition performance will definitely improved. From the results, its is observed that all the combinations explored in this have enhanced the recognition performance significantly.
作者: 漂浮    時間: 2025-3-25 01:53
Emotion Recognition on Real Life Emotions,motions. Single and multi-speaker data is collected to study the speaker influence on emotion recognition. Different features are explored for identifying the collected emotions. From the results, it is observed that spectral features carry robust emotion specific information.
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作者: 音樂學者    時間: 2025-3-25 09:47
Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features,cy cepstral?coefficients (MFCC) are used as the correlates of vocal tract information. In addition to LPCCs and MFCCs, formant related features are also explored in this work for recognizing emotions from speech. Extraction of the above mentioned spectral features is discussed in brief. Further extr
作者: 粗糙    時間: 2025-3-25 12:07
Robust Emotion Recognition using Sentence, Word and Syllable Level Prosodic Features,nize the emotions is illustrated using the gross statistics and time varying patterns of prosodic parameters. Prosodic correlates of speech such as energy, duration and pitch parameters are computed from the emotional utterances. Global prosodic features representing the gross statistics of prosody
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Emotion Recognition on Real Life Emotions,ns with reasonable accuracy. From the literature it is observed that combination of different features improves the classification performance. In this chapter score level combination of different features has been studied for recognizing real life emotions. For modelling real life emotions, there i
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K. Sreenivasa Rao,Shashidhar G. Koolagudin eingegangen wird, wurden aktualisiert, indem die aktuellen .EUROCODES .berücksichtigt sind. Das Kapitel 12, .überwachung ,Prüfung, Bewertung und Beurteilung von Brücken, .wird um den Abschnitt 12.7, .Kontinuierliche, rechnergestützte, Dauerüberwachung (Monitoring) .erweitert, indem an einem Beispi
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K. Sreenivasa Rao,Shashidhar G. Koolagudin eingegangen wird, wurden aktualisiert, indem die aktuellen .EUROCODES .berücksichtigt sind. Das Kapitel 12, .überwachung ,Prüfung, Bewertung und Beurteilung von Brücken, .wird um den Abschnitt 12.7, .Kontinuierliche, rechnergestützte, Dauerüberwachung (Monitoring) .erweitert, indem an einem Beispi
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K. Sreenivasa Rao,Shashidhar G. Koolagudind. Das Kapitel 12, .überwachung ,Prüfung, Bewertung und Beurteilung von Brücken, .wird um den Abschnitt 12.7, .Kontinuierliche, rechnergestützte, Dauerüberwachung (Monitoring) .erweitert, indem an einem Beispi978-3-658-03342-2
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Book 2019sses of speech processing and speech acquisition. This book is an introduction to the field and aimed at students and scientists in neuroscience, computer science, medicine, psychology and linguistics..




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