AURORA Project database - Subset of SpeechDat-Car - German database - Evaluation Package
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Base de données du projet AURORA - sous-ensemble de la base de données SpeechDat-Car de l'allemand - Package d'évaluation
ID:
ELRA-AURORA-CD0003_03
The Aurora project was originally set up to establish a world wide 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: Distributed Speech Recognition - Front-End Feature Extraction Algorithm & Compression Algorithm
- ETSI DES/STQ WI008: Distributed Speech Recognition - Advanced Feature Extraction Algorithm.
This database is a subset of the SpeechDat-Car database in German language which has been collected as part of the European Union funded SpeechDat-Car project. It contains isolated and connected German digits spoken in the following noise and driving conditions inside a car:
1. High speed good road
2. Low speed rough road
3. Stopped with motor running
4. Town traffic
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DESCRIPTION DISPONIBLE EN FRANCAIS PROCHAINEMENT.
The Aurora project was originally set up to establish a world wide 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: Distributed Speech Recognition - Front-End Feature Extraction Algorithm & Compression Algorithm
- ETSI DES/STQ WI008: Distributed Speech Recognition - Advanced Feature Extraction Algorithm.
This database is a subset of the SpeechDat-Car database in German language which has been collected as part of the European Union funded SpeechDat-Car project. It contains isolated and connected German digits spoken in the following noise and driving conditions inside a car:
1. High speed good road
2. Low speed rough road
3. Stopped with motor running
4. Town traffic
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