Mitigating the effects of non-stationary unseen noises on language recognition performance

We introduce a new dataset for the study of the effect of highly non-stationary noises on language recognition (LR) performance. The dataset is based on the data from the 2009 Language Recognition Evaluation organized by the National Institute of Standards and Technology (NIST). Randomly selected no...

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Detalles Bibliográficos
Autores principales: Ferrer, L., McLaren, M., Lawson, A., Graciarena, M., Noth E., Steidl S., Moller S., Ney H., Mobius B., Alibaba Group; Amazon; et al.; Facebook; Google; Telekom Innovation Laboratories
Formato: CONF
Materias:
Non-stationary noise
Speech activity detection
Spoken language recognition
Computational linguistics
Signal detection
Speech
Speech communication
Statistical tests
Data performance
Language recognition
Model Adaptation
National Institute of Standards and Technology
Nonstationary noise
Signaltonoise ratio (SNR)
Speech activity detections
Speech recognition
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_2308457X_v2015-January_n_p3446_Ferrer
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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