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Research Projects


Research Topics

We are interested in adaptive filtering algorithms for acoustic signals. Applications include

Acoustic Echo Canceller

Acoustic echo cancellation is important for audio teleconferencing when full-duplex transmission of speech is necessary. The objective of the echo canceller is to detect and remove echoes as quickly and effectively as possible, while minimizing any loss in voice quality due to the echo. The performance of the echo canceller should be robust to the presence of background noise, and more importantly, to the presence of near-end speech. Thus, it is important to handle the double-talk situation (a situation that both parties in the communication line are speaking at the same time).

Unlike the line echo which occurs with relatively short lengthes, the acoustic echo requires long-tap adaptive filters (several thousands-tap echo canceller is not uncommon), which raises computational and slow convergence problems.

Our research focuses on developing adaptive algorithms that can effectively solve the above mentioned problems.

Active Noise Control

Active Noise Cancellation (ANC) is a method of actively reducing undesired noise. ANC introduced a canceling ''antinoise'' wave using secondary sources (speakers). These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme.

Our study aims to develop adaptive algorithms that can be used for narrowband ANC systems

Adaptive Feedback Cancellation for Hearing Aids

Howling in hearing aids is caused by acoustic feedback from the receiver to the microphone. In practice, it not only limits the maximum usable gain but also degrades sound quality of the hearing aids. A common approach to this well-known problem is to use an adaptive feedback canceller (AFC), in which the entire e ect of feedback is eliminated by adaptively estimating the acoustic feedback path.

The most advanced feedback cancellation schemes monitor for feedback while the listener is wearing the hearing aid. The acoustic feedback is then estimated and eliminated by using an adaptive digital filter or notch filter. Important issue in feedback cancellation is that there exists correlation between the input and output signals, which deteriorates the performance of the adaptive feedback canceller.

Our research focuses on developing fast but simple adaptive algorithms that can be implementable on battery-powered digital hearing aids.

Binaural Speech Enhancement

By wearing hearing aids in both ears, it is much easier to understand speech in noisy environments. Further benefits for improving user comfort and speech intelligibility can be achieved by reducing the environmental noise. Real-life acoustic environment consist of various sound components such as desired speech signal, diffuse noise, and directional interference. Accordingly, the speech enhancement algorithms has to deal with all of the noise components in a unified framework.

Our research aim to develop unbiased target/noise PSD estimators for binaural digital hearing aids operating in complex acoustic noisy environment.

3-dimensional Audio Technologies

In analysis and synthesis of 3D audio scenes, extracting (or recording) the primary acoustic components with diractional information is very important to maintain high-fidelity audio. Our research focuses on extracting the primary components from stereo audio for applications such as stereo upmixing, binaural auralization, and object-based 3D rendering.

Related research topics are sound localization in multi-channel audio systems, crosstalk cancellation and room equalization filter design, bass enhancement for small-size speakers, and artificial reverberation for use in mobile devices.