Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Sound classification in hearing aids inspired by auditory scene analysis
EURASIP Journal on Applied Signal Processing
Rate-constrained collaborative noise reduction for wireless hearing aids
IEEE Transactions on Signal Processing
EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
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Abstract: Assisted by soft computing methods, the work we present in this paper focuses on the design of energy-efficient algorithms for binaural hearing aids that aim to separate speech from other sounds the hearing impaired person is not interested in. To do this, the right and left hearing aids need to wirelessly transmit to each other some parameters involved in the speech separation algorithm. The problem is that this transmission appreciably reduces the battery life, the most important constrain for designing advanced algorithms in hearing aids. Reducing the number of bits used to represent the parameters to be transmitted will bring down the power consumption, but at the expense of degrading the ability of the system to separate the speech from the other sound sources. Aiming at solving this problem, our approach, based on quantizing the parameters to be transmitted, basically consists in computing the adequate number of quantization bits by means of a combination of neural networks and genetic algorithms in the effort of finding a balance between low bit rate (and thus, low power consumption) and good separation of speech. The results show that even by using only 2bits/quantized-sample, the quality of the separation is as high as 70% of the limiting non-quantized quality separation factor, which has been found to be 85%.