Learn More
An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated(More)
We present an algorithm for removing environmental noise from neurophysiological recordings such as magnetoencephalography (MEG). Noise fields measured by reference magnetometers are optimally filtered and subtracted from brain channels. The filters (one per reference/brain sensor pair) are obtained by delaying the reference signals, orthogonalizing them to(More)
A model of pitch perception is presented involving an array of delay lines and inhibitory gating neurons. In response to a periodic sound, a minimum appears in the pattern of outputs of the inhibitory neurons at a lag equal to the period of the sound. The position of this minimum is the cue to pitch. The model is similar to the autocorrelation model of(More)
We present a method for removing unwanted components of biological origin from neurophysiological recordings such as magnetoencephalography (MEG), electroencephalography (EEG), or multichannel electrophysiological or optical recordings. A spatial filter is designed to partition recorded activity into stimulus-related and stimulus-unrelated components, based(More)
Auditory environments vary as a result of the appearance and disappearance of acoustic sources, as well as fluctuations characteristic of the sources themselves. The appearance of an object is often manifest as a transition in the pattern of ongoing fluctuation, rather than an onset or offset of acoustic power. How does the system detect and process such(More)
Sensitivity to the similarity of the acoustic waveforms at the two ears, and specifically to changes in similarity, is crucial to auditory scene analysis and extraction of objects from background. Here, we use the high temporal resolution of magnetoencephalography to investigate the dynamics of cortical processing of changes in interaural correlation, a(More)
Vowel identity correlates well with the shape of the transfer function of the vocal tract, in particular the position of the first two or three formant peaks. However, in voiced speech the transfer function is sampled at multiples of the fundamental frequency (F0), and the short-term spectrum contains peaks at those frequencies, rather than at formants. It(More)
An experiment investigated the effects of amplitude ratio (-35 to 35 dB in 10-dB steps) and fundamental frequency difference (0%, 3%, 6%, and 12%) on the identification of pairs of concurrent synthetic vowels. Vowels as weak as -25 dB relative to their competitor were easier to identify in the presence of a fundamental frequency difference (delta F0).(More)
This paper proposes a novel F<sub>0</sub> contour estimation algorithm based on a precise parametric description of the voiced parts of speech derived from the power spectrum. The algorithm is able to perform in a wide variety of noisy environments as well as to estimate the F<sub>0</sub>s of cochannel concurrent speech. The speech spectrum is modeled as a(More)
We present a method to remove the effects of sensor-specific noise in multiple-channel recordings such as magnetoencephalography (MEG) or electroencephalography (EEG). The method assumes that every source of interest is picked up by more than one sensor, as is the case with systems with spatially dense sensors. To reduce noise, each sensor signal is(More)