Base de données du projet AURORA - Aurora 4a - Package d'évaluation
ID:
ELRA-AURORA-CD0004_01
The Aurora project was originally set up to establish a worldwide standard for the feature extraction software which forms the core of the front-end of a DSR (Distributed Speech Recognition) system. ETSI formally adopted this activity as work items 007 and 008.
The two work items within ETSI are : ETSI DES/STQ WI007 : DSR - Front-end feature extraction algorithm & compression algorithm ETSI DES/STQ WI008 : DSR - Advanced feature extraction algorithm
The Aurora project has released a number of list files for performing the training and testing on the Wall Street Journal (WSJ0) data at two sampling rates -8 kHz and 16 kHz. The Aurora 4a database is based on the WSJ0 with artificial addition of noise over a range of signal to noise ratios. It contains both clean and multicondition training sets and 14 evaluation sets with different noise types and microphones.
Two original copies of the contract (pdf | doc | rtf) must be sent to ELDA.
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DESCRIPTION DISPONIBLE EN FRANCAIS PROCHAINEMENT.
The Aurora project was originally set up to establish a worldwide standard for the feature extraction software which forms the core of the front-end of a DSR (Distributed Speech Recognition) system. ETSI formally adopted this activity as work items 007 and 008.
The two work items within ETSI are : ETSI DES/STQ WI007 : DSR - Front-end feature extraction algorithm & compression algorithm ETSI DES/STQ WI008 : DSR - Advanced feature extraction algorithm
The Aurora project has released a number of list files for performing the training and testing on the Wall Street Journal (WSJ0) data at two sampling rates -8 kHz and 16 kHz. The Aurora 4a database is based on the WSJ0 with artificial addition of noise over a range of signal to noise ratios. It contains both clean and multicondition training sets and 14 evaluation sets with different noise types and microphones.
Two original copies of the contract (pdf | doc | rtf) must be sent to ELDA.
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