Jason Wung

Inter-channel decorrelation by sub-band resampling in frequency domain

This paper presents a novel decorrelation procedure by frequency-domain resampling in sub-bands. The new procedure expands on the idea of resampling in the frequency domain that efficiently and effectively alleviates the non-uniqueness problem for a multi-channel acoustic echo cancellation system while introducing minimal distortion to the signal. We show in theory and verify experimentally that the amount of decorrelation in each sub-band, measured in terms of the coherence, can be controlled arbitrarily by varying the resampling ratio per frequency bin. For perceptual evaluation, we adjust the sub-band resampling ratios to match the coherence given by other decorrelation procedures. The speech quality (PESQ) score from the proposed decorrelation procedure remains high at around 4.5, which is about the highest possible PESQ score after signal modification.

Decorrelation by resampling in frequency domain for multi-channel acoustic echo cancellation based on residual echo enhancement

An inter-channel decorrelation procedure via resampling in the frequency domain for multi-channel acoustic echo cancellation (MCAEC) based on residual echo enhancement is proposed. The objective is to efficiently alleviate the non-uniqueness problem while introducing minimal distortion to the audio quality and the signal statistics. The effectiveness is illustrated with respect to the standard approach of using a memoryless nonlinearity or additive noise. A combination of the new decorrelation procedure and the residual echo enhancement technique points towards a computationally feasible yet very robust frequency-domain MCAEC system.

A system approach to residual echo suppression in robust hands-free teleconferencing

This paper presents a system approach to the residual echo suppression (RES) problem in a noisy acoustic environment. We propose a method that takes advantage of our existing robust acoustic echo cancellation system in order to obtain a residual echo estimate that closely resembles the true, noise-free residual echo. To achieve improved RES during strong near-end interference (e.g., double talk), a psychoacoustic postfilter is also used. The simulation results show that our RES based on the system approach outperforms a conventional estimation method. Comparing the postfiltered output to the unprocessed one indicates that our proposed RES approach can raise the PESQ score by more than half a point.

A system approach to acoustic echo cancellation in robust hands-free teleconferencing

This paper presents a system approach to the acoustic echo cancellation (AEC) problem in a noisy acoustic environment. We propose a method that makes use of the estimated near-end signal from a postfilter to further improve the AEC system performance. The cancellation performance is enhanced especially during strong near-end interference (e.g., double talk). Simulation results show that our stereophonic AEC based on the system approach with postfilter integration outperforms the one using the original robust AEC system by itself without postfilter integration. The improved performance is noted especially during double talk, where simulation results show that the true echo return loss enhancement can be boosted by as much as 10 dB.

Tuning methodology for speech enhancement algorithms using a simulated conversational database and perceptual objective measures

In this paper, we propose a formal methodology for tuning the parameters of a single-microphone speech enhancement system for hands-free devices. The tuning problem is formulated as a large-scale nonlinear programming problem that is solved by a genetic algorithm to determine the global solution. A conversational speech database is automatically generated by modeling the interactivity in telephone conversations, and perceptual objective quality measures are used as the optimization criteria for the automated tuning over the generated database. A subjective listening test is then performed by comparing the automatically tuned system based on objective criteria to the system tuned by expert human listeners. Subjective and objective evaluation result shows that the proposed automated tuning methodology greatly improves the enhanced speech quality, potentially saving resources over manual evaluation, speeding up development and deployment time, and guiding the algorithmic design.

Speech enhancement using minimum mean-square error estimation and a post-filter derived from vector quantization of clean speech

In this paper, a novel post-filtering method applied after the logSTSA filter is proposed. Since the post-filter is derived from vector quantization of clean speech database, it has an equivalent effect of imposing clean source spectral constraints on the enhanced speech. When combined with the logSTSA filter, the additional filter can noticeably suppress residual artifacts by effectively lowering the residual white noise of decision-directed estimation as well as reducing the musical noise of maximum likelihood estimation. Compared to the logSTSA enhanced speech, the overall enhanced speech is able to raise the PESQ score by nearly half a point.

On the performance of the robust acoustic echo cancellation system with decorrelation by sub-band resampling

This paper examines the effect of inter-channel decorrelation by sub-band resampling (SBR) on the performance of the robust acoustic echo cancellation (AEC) system based on the residual echo enhancement technique. Due to the flexibility of SBR, the decorrelation performance as measured by the coherence can be matched with other conventional decorrelation procedures. Given the same degree of decorrelation, we have shown previously that SBR achieves superior audio quality compared to other procedures. We show in this paper that SBR also provides higher stereophonic AEC performance in a very noisy condition, where the performance is evaluated by decomposing the true echo return loss enhancement and the misalignment per sub-band to better demonstrate the superiority of our decorrelation procedure over other methods.

Robust acoustic echo cancellation in the short-time fourier transform domain using adaptive crossband filters

This paper presents a robust acoustic echo cancellation (AEC) system in the short-time Fourier transform (STFT) domain using adaptive crossband filters. The STFT-domain AEC allows for a simpler system structure compared to the traditional frequency-domain AEC, which normally requires several applications of the discrete Fourier transform (DFT) and the inverse DFT, while the robust AEC (RAEC) allows for continuous and stable filter updates during double talk without freezing the adaptive filter. The RAEC and the STFT-domain AEC have been investigated in the past in separate studies. In this work we propose a novel algorithm that combines the advantages of both approaches for robust update of the adaptive crossband filters even during double talk. Experimental results confirm the benefit of incorporating the robustness constraint for the adaptive crossband filters and show improved performance in terms of the echo reduction and the predicted sound quality.

Inter-Channel Decorrelation by Sub-Band Resampling for Multi-Channel Acoustic Echo Cancellation

An inter-channel decorrelation procedure is highly recommended for multi-channel acoustic echo cancellation (AEC) to directly assist adaptive filtering algorithms in overcoming the so-called “non-uniqueness” problem. Although various methods have been proposed in the past to mitigate the problem and lower the misalignment of the adaptive filter, the introduced audible distortion often limits the effectiveness of those algorithms. In this paper, we investigate in detail the decorrelation by resampling technique and a proper design strategy for sub-band resampling (SBR), which permits finely tuned, frequency specific control of the trade-off between decorrelation, measured in terms of the (magnitude-squared) coherence, and audio quality, evaluated in terms of objective speech quality measures and a subjective listening test. Our most recent study provides a deep analysis of the performance bounds of the resampling procedure by analyzing the relationship between resampling, coherence, and achievable steady-state misalignment. We provide a novel, theoretically justifiable, and perceptually motivated strategy for SBR to achieve a fast multi-channel AEC convergence rate while maintaining the highest audio quality when compared to other conventional decorrelation procedures.

A probabilistic approach to acoustic echo clustering and suppression

This paper introduces an approach to cluster and suppress acoustic echo signals in hands-free, full-duplex speech communication systems. We employ the instantaneous recursive estimate of the magnitude squared coherence (MSC) of the echo line signal and the microphone signal, and model it with a two-component Beta mixture distribution. Since we consider the case of multiple microphone pickup, we further integrate the normalized recording vector as location feature into the proposed approach to achieve reliable soft decisions on the echo presence. The location information has been widely used for clustering-based blind source separation, and can be modeled using a Watson mixture distribution. Simulation evaluations of the proposed method show that it can achieve significant echo suppression performance.