The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a novel frequency based oscilloscope triggering technique for measurements involving complex waveforms that are challenging even today. Proposed technique is capable of providing stable triggering even in the case of complex periodic waveforms category where commonly used level triggering scheme fail to perform adequately and may be used in problem of estimating many typical signal...
In this paper, we present a robust spectro-temporal feature extraction technique using autoregressive models (AR) of sub-band Hilbert envelopes. AR models of Hilbert envelopes are derived using frequency domain linear prediction (FDLP). From the sub-band Hilbert envelopes, spectral features are derived by integrating these envelopes in short-term frames and the temporal features are formed by converting...
In this paper, we present a new noise compensation technique for modulation frequency features derived from syllable length segments of subband temporal envelopes. The subband temporal envelopes are estimated using frequency domain linear prediction (FDLP). We propose a technique for noise compensation in FDLP where an estimate of the noise envelope is subtracted from the noisy speech envelope. The...
Frequency domain linear prediction (FDLP) represents an efficient technique for representing the long-term amplitude modulations (AM) of speech/audio signals using autoregressive models. For the proposed analysis technique, relatively long temporal segments (1000 ms) of the input signal are decomposed into a set of sub-bands. FDLP is applied on each sub-band to model the temporal envelopes. The residual...
We present a new feature extraction technique for phoneme recognition that uses short-term spectral envelope and modulation frequency features. These features are derived from sub-band temporal envelopes of speech estimated using frequency domain linear prediction (FDLP). While spectral envelope features are obtained by the short-term integration of the sub-band envelopes, the modulation frequency...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.