S. Goetze, K.-D. Kammeyer, and V. Mildner, “Multi-Channel Noise-Reduction-Systems for Speaker Identification in an Automotive Acoustic Environment,” in Proc. AES Convention 120, May 2006, Paper 6756. [Online]. Available: https://aes.org/publications/elibrary-page/?id=13560
Goetze S, Kammeyer KD, Mildner V. Multi-Channel Noise-Reduction-Systems for Speaker Identification in an Automotive Acoustic Environment. In: AES Convention 120. Audio Engineering Society; 2006. Paper 6756. Available from: https://aes.org/publications/elibrary-page/?id=13560
@inproceedings{Goetze2006_13560,
author = {Goetze, Stefan and Kammeyer, Karl-Dirk and Mildner, Volker},
title = {{Multi-Channel Noise-Reduction-Systems for Speaker Identification in an Automotive Acoustic Environment}},
booktitle = {AES Convention 120},
note = {Paper 6756},
year = {2006},
month = may,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=13560}
}
TY - CPAPER
TI - Multi-Channel Noise-Reduction-Systems for Speaker Identification in an Automotive Acoustic Environment
AU - Goetze, Stefan
AU - Kammeyer, Karl-Dirk
AU - Mildner, Volker
T2 - AES Convention 120
M1 - Paper 6756
PY - 2006
DA - 2006/05/06
UR - https://aes.org/publications/elibrary-page/?id=13560
PB - Audio Engineering Society
LA - en
AB - Devices for communication and information utilised by car drivers are facing two essential requirements: hands-free operation via distant microphones but also robustness against different noises depending on car speed etc. Automatic speaker identification can be utilized within such devices to either supply speech recognition systems with so called apriori information to achieve higher recognition rates or even to enable applications such as heating systems to adjust to the preferences of the driver. Thus identifying the driver from a predefined group of possible system users may be a task for future applications. The aim in this work is to investigate to which extent multi-channel noise reduction systems are suitable for improving the performance of speaker identification algorithms under different acoustic conditions in an automotive environment.
ER -