Previous studies have shown that infants use prosodic information as an aid for discriminating and recognising words. The present work is based on a word learning model which automatically extracts target words from raw speech input paired with a label for the target word. This model was enhanced by incorporating prosodic information. In addition, an unsupervised model is developed which does not rely on a label of any kind. Although prosodic information could not improve the performance of the unsupervised model, it is shown that the incorporation of pitch leads to an increase of performance in the supervised case and that the unsupervised model yields effective results.
"Sinopsis" puede pertenecer a otra edición de este libro.
Previous studies have shown that infants use prosodic information as an aid for discriminating and recognising words. The present work is based on a word learning model which automatically extracts target words from raw speech input paired with a label for the target word. This model was enhanced by incorporating prosodic information. In addition, an unsupervised model is developed which does not rely on a label of any kind. Although prosodic information could not improve the performance of the unsupervised model, it is shown that the incorporation of pitch leads to an increase of performance in the supervised case and that the unsupervised model yields effective results.
Born 1988 in Rostock, Germany, Daniel Berndt studied Cognitive Science in Osnabrück and Artificial Intelligence in Edinburgh. He became co-founder of Codeus, a developing company applying techniques from AI and Computational Linguistics and continues to work in his field of interest.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: moluna, Greven, Alemania
Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Berndt DanielBorn 1988 in Rostock, Germany, Daniel Berndt studied Cognitive Science in Osnabrueck and Artificial Intelligence in Edinburgh. He became co-founder of Codeus, a developing company applying techniques from AI and Computa. Nº de ref. del artículo: 4976750
Cantidad disponible: Más de 20 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Previous studies have shown that infants use prosodic information as an aid for discriminating and recognising words. The present work is based on a word learning model which automatically extracts target words from raw speech input paired with a label for the target word. This model was enhanced by incorporating prosodic information. In addition, an unsupervised model is developed which does not rely on a label of any kind. Although prosodic information could not improve the performance of the unsupervised model, it is shown that the incorporation of pitch leads to an increase of performance in the supervised case and that the unsupervised model yields effective results. Nº de ref. del artículo: 9783639314144
Cantidad disponible: 2 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Word Learning with Prosodic information | Applying non-verbal Cues to enhance Speech Recognition Performance | Daniel Berndt | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639314144 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 107175266
Cantidad disponible: 5 disponibles
Librería: Mispah books, Redhill, SURRE, Reino Unido
paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Nº de ref. del artículo: ERICA829363931414X6
Cantidad disponible: 1 disponibles