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This paper describes a semi-automatic system to capture and label a reasonable size biometric database. In our case, the biometric to be assessed are footstep signals, but the system could be extendable to other biometrics. Extra biometric data such as the voice and video recordings of the face and the gait are used to assist the database labelling to minimise the error. Thus, audio identifier recordings...
Embedded speaker recognition in mobile devices could involve several ergonomic constraints and a limited amount of computing resources. Even if they have proved their efficiency in more classical contexts, GMM/UBM based systems show their limits in such situations, with good accuracy demanding a relatively large quantity of speech data, but with negligible harnessing of linguistic content. The proposed...
This paper investigates the accuracy of automatic speech recognition (ASR) and 6 other well-reported objective quality measures for the task of estimating speech intelligibility. It is believed to be the first assessment of such a range of measures side-by-side and in the context of intelligibility. A total of 39 degradation conditions including those from a newly proposed low bit rate (0.3 to 1.5...
As with many approaches to noise robust automatic speech recognition (ASR) the benefits of spectral subtraction tend to diminish as noise levels in the order of 0 dB are approached. Whilst the majority of related work focuses on reducing magnitude errors a number of new approaches addressing the often overlooked, additional sources of error have appeared in the literature in recent years. Relatively...
Power spectra may be computed via a discrete fourier transform with severely rounded-off trigonometric terms, and recently the ultimate round-off ?? that is to rectangular waves ?? has been proposed.1 A comparison is made between this and a 3 level round-off, +1, ??1 and 0.
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