A Neural Network Trained Microphone Array System for Noise Reduction
| Document type: | Conference Papers |
|---|---|
| Peer reviewed: | Yes |
| Author(s): | Mattias Dahl, Ingvar Claesson |
| Title: | A Neural Network Trained Microphone Array System for Noise Reduction |
| Conference name: | 1996 IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing (NNSP96) |
| Year: | 1996 |
| Pagination: | 311-319 |
| Publisher: | IEEE |
| City: | Kyoto, Japan |
| ISI number: | A1996BG22Q00032 |
| Organization: | Blekinge Institute of Technology |
| Department: | Dept. of Signal Processing (Institutionen för signalbehandling) Dept. of Signal Processing S-372 25 Ronneby +46 455 780 00 http://www.hk-r.se/isb/isb_en.html |
| Authors e-mail: | Mattias.Dahl@isb.hk-r.se |
| Language: | English |
| Abstract: | This paper presents a neural network based microphone array system, which is capable to continuously perform speech enhancement and adaptation to nonuniform quantization, such as A-law and $mu@-law. Such a quantizer is designed to increase the Signal to Quantization Noise Ratio (SQNR) for small amplitudes in telecommunications systems. The proposed method primarily developed for hands-free mobile telephones, suppresses the ambient car noise with approximately 10 dB. The system is based upon a multi-layered nonlinear back-propagation trained network by using a built-in calibration technique. |
| Subject: | Signal Processing\Beamforming Signal Processing\Speech Enhancement |
| Keywords: | Microphones, Interference suppression, Speech analysis, Signal to noise ratio, Cellular telephone systems, Backpropagation, Algorithms |
