Cortical transformation of spatial processing for solving the cocktail party problem: a computational model(1,2,3).

In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural time differences (ITDs) are well understood in precortical areas, how such information is reused and transformed in higher cortical regions to represent segregated sound sources is not clear. We present a computational model describing a hypothesized neural network that spans spatial cue detection areas and the cortex. This network is based on recent physiological findings that cortical neurons selectively encode target stimuli in the presence of competing maskers based on source locations (Maddox et al., 2012). We demonstrate that key features of cortical responses can be generated by the model network, which exploits spatial interactions between inputs via lateral inhibition, enabling the spatial separation of target and interfering sources while allowing monitoring of a broader acoustic space when there is no competition. We present the model network along with testable experimental paradigms as a starting point for understanding the transformation and organization of spatial information from midbrain to cortex. This network is then extended to suggest engineering solutions that may be useful for hearing-assistive devices in solving the cocktail party problem.R01 DC000100 - NIDCD NIH HHSPublished versio

No-Arbitrage Taylor Rules

We estimate Taylor (1993) rules and identify monetary policy shocks using no-arbitrage pricing techniques. Long-term interest rates are risk-adjusted expected values of future short rates and thus provide strong over-identifying restrictions about the policy rule used by the Federal Reserve. The no-arbitrage framework also accommodates backward-looking and forward-looking Taylor rules. We find that inflation and output gap account for over half of the variation of time-varying excess bond returns and most of the movements in the term spread. Taylor rules estimated with no-arbitrage restrictions differ from Taylor rules estimated by OLS, and the resulting monetary policy shocks are somewhat less volatile than their OLS counterparts.

A physiologically inspired model for solving the cocktail party problem.

At a cocktail party, we can broadly monitor the entire acoustic scene to detect important cues (e.g., our names being called, or the fire alarm going off), or selectively listen to a target sound source (e.g., a conversation partner). It has recently been observed that individual neurons in the avian field L (analog to the mammalian auditory cortex) can display broad spatial tuning to single targets and selective tuning to a target embedded in spatially distributed sound mixtures. Here, we describe a model inspired by these experimental observations and apply it to process mixtures of human speech sentences. This processing is realized in the neural spiking domain. It converts binaural acoustic inputs into cortical spike trains using a multi-stage model composed of a cochlear filter-bank, a midbrain spatial-localization network, and a cortical network. The output spike trains of the cortical network are then converted back into an acoustic waveform, using a stimulus reconstruction technique. The intelligibility of the reconstructed output is quantified using an objective measure of speech intelligibility. We apply the algorithm to single and multi-talker speech to demonstrate that the physiologically inspired algorithm is able to achieve intelligible reconstruction of an "attended" target sentence embedded in two other non-attended masker sentences. The algorithm is also robust to masker level and displays performance trends comparable to humans. The ideas from this work may help improve the performance of hearing assistive devices (e.g., hearing aids and cochlear implants), speech-recognition technology, and computational algorithms for processing natural scenes cluttered with spatially distributed acoustic objects.R01 DC000100 - NIDCD NIH HHSPublished versio

CW-pumped telecom band polarization entangled photon pair generation in a Sagnac interferometer

A polarization entangled photon pair source is widely used in many quantum information processing applications such as teleportation, quantum swapping, quantum computation and high precision quantum metrology. Here, we report on the generation of a continuous-wave pumped degenerated 1550 nm polarization entangled photon pair source at telecom wavelength using a type-II phase-matched periodically poled KTiOPO4 crystal in a Sagnac interferometer. Hong-Ou-Mandel-type interference measurement shows the photon bandwidth of 2.4 nm. High quality of entanglement is verified by various kinds of measurements, for example two-photon interference fringes, Bell inequality and quantum states tomography. The wavelength of photons can be tuned over a broad range by changing the temperature of crystal or pump power without losing the quality of entanglement. This source will be useful for building up long-distance quantum networks

An Effective Combination of Different Order N-grams

In this paper an approach is proposed to combine different order N-grams based on the discriminative estimation criterion, on which the parameters of n-gram can be optimized. To raise the power of modeling language information, we propose several schemes to combine conventional different order n-gram language model. We employ Newton Gradient method to estimate the assumption probabilities and then test the optimally selected language model. We conduct experiments on the platform of conversion from Chinese pinyin to Chinese character. The experimental results show that the memory capacity of language model can be remarkably lowered with hide loss of accuracy. 1