EAN: 9783844088090

FRONT-END SIGNAL PROCESSING FOR FAR-FIELD SPEEC...

Devices for speech communication operated in handsfree mode offer a very natural way of human
communication. However  the signal-to-noise ratio (SNR) at the microphones of the device is
typically low. This requires appropriate front-end signal processing (FESP) to enhance the
desired speech signal.A beamformer (BF) can use the microphones of multiple devices to
compensate for the low initial SNR  if all microphone positions are known. For estimating these
positions the novel orthogonal geometric projection (OGP) is proposed as an approach with low
user effort.For allowing a full-duplex speech communication  one acoustic echo canceller (AEC)
per microphone channel is usually employed prior to the BF  which results in a high complexity.
Therefore  change prediction (ChaP) is proposed that enables the use of a single AEC after the
BF. By collecting information on the acoustic system over time  ChaP can facilitate the
adaptation of the AEC such that this low-complexity single-AEC configuration can approach the
performance of the high-complexity multi-AEC variant.Conventional linear AEC is actually
insufficient for mobile consumer devices  because their low-cost loudspeakers and amplifiers
show a significant nonlinear behavior. The novel dual-stage multi-channel Kalman
(DualStage-MCK) algorithm also compensates for these nonlinear effects and does not suffer from
limited modelling capabilities  slow tracking or high computational complexity  which are
typical drawbacks of state-of-the-art solutions.The performance of the proposed solutions is
evaluated in typical use cases and on realistic test data that includes device-specific
acoustic shadowing and nonlinear effects acquired from specifically manufactured tablet  smart
speaker and smartphone mockups.

Aktuelle Preise zur EAN 9783844088090

Produktinformationen zur 9783844088090