In this paper, the design, implementation and testing of a digital microphone array is presented. The array uses digital MEMS microphones which integrate the microphone, amplifier and analogue to digital converter on a single chip in place of the analogue microphones and external audio interfaces currently used. The device has the potential to be smaller, cheaper and more flexible than typical analogue arrays, however the effect on speech recognition performance of using digital microphones is as yet unknown. In order to evaluate the effect, an analogue array and the new digital array are used to simultaneously record test data for a speech recognition experiment. Initial results employing no adaptation show that performance using the digital array is significantly worse (14% absolute WER) than the analogue device. Subsequent experiments using MLLR and CMLLR channel adaptation reduce this gap, and employing MLLR for both channel and speaker adaptation reduces the difference between the arrays to 4.5% absolute WER.

This paper presents a new corpus comprising single and overlapping speech recorded using digital MEMS and analogue microphone arrays. In addition to this, the paper presents results from speech separation and recognition experiments on this data. The corpus is a reproduction of the multichannel Wall Street Journal audio-visual corpus (MC-WSJ-AV), containing recorded speech in both a meeting room and an anechoic chamber using two different microphone types as well as two different array geometries. The speech separation and speech recognition experiments were performed using SRP-PHAT-based speaker localisation, superdirective beamforming and multiple post-processing schemes, such as residual echo suppression and binary masking. Our simple, cMLLR-based recognition system matches the performance of state-of-the-art ASR systems on the single speaker task and outperforms them on overlapping speech. The corpus will be made publicly available via the LDC in spring 2013.

There is a continuous drive for methodologies and approaches of low power design. This is mainly driven by the surge in portable computing. On the other hand, the design of low power systems for different portable applications is not a simple task. This is because of the number of constraints that influence the power consumption of a device. In addition to issues of performance and functionality, there is a need to satisfy strict test coverage constraints. The authors investigate the impact of DSP architectural realisation, multiplier type, and the choice of number representation on the overall power consumption of DSP devices. Work in the literature so far has concentrated on the effect of these on a part or a section of a DSP system. Furthermore the effect of DfT circuits on the overall performance is studied. A hearing aid device is considered as an example of a system with strict power/area constraints. It is shown that the choice of multiplier architecture and number representation should be carefully considered when specific DSP architectural choices are made. The results are demonstrated with a number of specially designed DSP architectures for the implementation of FIR filtering algorithms on hearing aid devices.

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This paper examines the effect of sensor performance on speaker diarisation in meetings and investigates the use of more advanced beamforming techniques, beyond the typically employed delay-sum beamformer, for mitigating the effects of poorer sensor performance. We present superdirective beamforming and investigate how different time difference of arrival (TDOA) smoothing and beamforming techniques influence the performance of state-of-the-art diarisation systems. We produced and transcribed a new corpus of meetings recorded in the instrumented meeting room using a high SNR analogue and a newly developed low SNR digital MEMS microphone array (DMMA.2). This research demonstrates that TDOA smoothing has a significant effect on the diarisation error rate and that simple noise reduction and beamforming schemes suffice to overcome audio signal degradation due to the lower SNR of modern MEMS microphones.Index Terms-Speaker diarisation in meetings, digital MEMS microphone array, time difference of arrival (TDOA), superdirective beamforming