New waves of consumer-centric applications, such as voice search and voice interaction
with mobile devices and home entertainment systems, increasingly require automatic …

Popular music is often composed of an accompaniment and a lead component, the latter
typically consisting of vocals. Filtering such mixtures to extract one or both components has …

A time-varying Wiener filter specifies the ratio of a target signal and a noisy mixture in a local
time-frequency unit. We estimate this ratio using a binaural processor and derive a ratio time …

Conventional speaker recognition systems perform poorly under noisy conditions. Inspired
by auditory perception, computational auditory scene analysis (CASA) typically segregates …

A conventional automatic speech recognizer does not perform well in the presence of noise,
while human listeners are able to segregate and recognize speech in noisy conditions. We …

In this article we have reviewed a wide variety of techniques based on the identification of
missing spectral features that have proved effective in reducing the error rates of automatic …

The performance of speaker recognition systems drop significantly under noisy conditions.
To improve robustness, we have recently proposed novel auditory features and a robust …

An effective way to increase the noise robustness of automatic speech recognition is to label
noisy speech features as either reliable or unreliable (missing), and to replace (impute) the …

A conventional automatic speech recognizer does not perform well in the presence of
multiple sound sources, while human listeners are able to segregate and recognize a signal …

The fields of human speech recognition (HSR) and automatic speech recognition (ASR)
both investigate parts of the speech recognition process and have word recognition as their …