82,586 research outputs found

    Block-Online Multi-Channel Speech Enhancement Using DNN-Supported Relative Transfer Function Estimates

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    This work addresses the problem of block-online processing for multi-channel speech enhancement. Such processing is vital in scenarios with moving speakers and/or when very short utterances are processed, e.g., in voice assistant scenarios. We consider several variants of a system that performs beamforming supported by DNN-based voice activity detection (VAD) followed by post-filtering. The speaker is targeted through estimating relative transfer functions between microphones. Each block of the input signals is processed independently in order to make the method applicable in highly dynamic environments. Owing to the short length of the processed block, the statistics required by the beamformer are estimated less precisely. The influence of this inaccuracy is studied and compared to the processing regime when recordings are treated as one block (batch processing). The experimental evaluation of the proposed method is performed on large datasets of CHiME-4 and on another dataset featuring moving target speaker. The experiments are evaluated in terms of objective and perceptual criteria (such as signal-to-interference ratio (SIR) or perceptual evaluation of speech quality (PESQ), respectively). Moreover, word error rate (WER) achieved by a baseline automatic speech recognition system is evaluated, for which the enhancement method serves as a front-end solution. The results indicate that the proposed method is robust with respect to short length of the processed block. Significant improvements in terms of the criteria and WER are observed even for the block length of 250 ms.Comment: 10 pages, 8 figures, 4 tables. Modified version of the article accepted for publication in IET Signal Processing journal. Original results unchanged, additional experiments presented, refined discussion and conclusion

    Low-complexity medium access control protocols for QoS support in third-generation radio access networks

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    One approach to maximizing the efficiency of medium access control (MAC) on the uplink in a future wideband code-division multiple-access (WCDMA)-based third-generation radio access network, and hence maximize spectral efficiency, is to employ a low-complexity distributed scheduling control approach. The maximization of spectral efficiency in third-generation radio access networks is complicated by the need to provide bandwidth-on-demand to diverse services characterized by diverse quality of service (QoS) requirements in an interference limited environment. However, the ability to exploit the full potential of resource allocation algorithms in third-generation radio access networks has been limited by the absence of a metric that captures the two-dimensional radio resource requirement, in terms of power and bandwidth, in the third-generation radio access network environment, where different users may have different signal-to-interference ratio requirements. This paper presents a novel resource metric as a solution to this fundamental problem. Also, a novel deadline-driven backoff procedure has been presented as the backoff scheme of the proposed distributed scheduling MAC protocols to enable the efficient support of services with QoS imposed delay constraints without the need for centralized scheduling. The main conclusion is that low-complexity distributed scheduling control strategies using overload avoidance/overload detection can be designed using the proposed resource metric to give near optimal performance and thus maintain a high spectral efficiency in third-generation radio access networks and that importantly overload detection is superior to overload avoidance
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