AES E-Library

AES E-Library

Dual Filtering Technique for Speech Signal Enhancements

Hands free applications in automobiles, such as voice recognition and Bluetooth communications, have been one of the great features added to vehicles’ infotainment systems. However, cabin and road noises degrade audio quality and negatively impact consumers’ experience. Research has been conducted and several noise reduction techniques have been proposed. However, due to the complexity of noise environments inside and outside vehicles, the hands free sounds quality still poses an issue for consumers. This continuously existed problem requires more research in this field. This paper proposes a novel technique to reduce noise and enhance voice recognition and Bluetooth audio quality in vehicles’ hands free applications. It utilizes the dual Kalman Filtering (KF) technique to suppress noise. This method has been validated using a MATLAB/SIMULINK simulation environment, which showed improvements in noise reductions in both Gaussian and non-Gaussian environments.

AES Convention: eBrief:
Publication Date:

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

The Engineering Briefs at this Convention were selected on the basis of a submitted synopsis, ensuring that they are of interest to AES members, and are not overly commercial. These briefs have been reproduced from the authors' advance manuscripts, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for their contents. Paper copies are not available, but any member can freely access these briefs. Members are encouraged to provide comments that enhance their usefulness.

Start a discussion about this paper!

AES - Audio Engineering Society