People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device integrated into a pair of headphones. In a user study of the proposed system, participants were asked to pay attention to one of three musical instruments playing simultaneously from separate spatial directions. We used a stimulus reconstruction method to decode attention from EEG signals. Results show that the proposed system can achieve good decoding accuracy (>70%) while providing superior user-friendliness compared to a traditional EEG setup.

Many signals are naturally described by continuous contours in the time-frequency plane, but standard time-frequency methods disassociate continuous structures into isolated “atoms” of energy. Here we propose a method that represents any discrete time-series as a set of time-frequency contours. The edges of the contours are defined by fixed points of a generalized reassignment algorithm. These edges are linked together by continuity such that each contour represents a single phase-coherent region of the time-frequency plane. By analyzing the signal across many time-scales, an over-complete set of contours is generated, and from this redundant set of shapes the simplest, most parsimonious forms may be selected. The result is an adaptive time-frequency analysis that can emphasize the continuity of long-range structure. The proposed method is demonstrated with a few examples.

This paper examines the performance of several source separation systems on a speech separation task for which human intelligibility has previously been measured. For anechoic mixtures, automatic speech recognition (ASR) performance on the separated signals is quite similar to human performance. In reverberation, however, while signal separation has some benefit for ASR, the results are still far below those of human listeners facing the same task. Performing this same experiment with a number of oracle masks created witha prioriknowledge of the separated sources motivates a new objective measure of separation performance, the Direct-path, Early echo, and Reverberation, of the Target and Masker (DERTM), which is closely related to the ASR results. This measure indicates that while the non-oracle algorithms successfully reject the direct-path signal from the masking source, they reject less of its reverberation, explaining the disappointing ASR performance.

Spatial auditory displays have received a great deal of attention in the community investigating how to present information through sound. This short commentary discusses our 2001 ICAD paper (Shinn-Cunningham, Streeter, and Gyss), which explored whether it is possible to provide enhanced spatial auditory information in an auditory display. The discussion provides some historical context and discusses how work on representing information in spatial auditory displays has progressed over the last 5 years.

Often, virtual acoustic environments present cues that are inconsistent with an individual's normal experiences. Through training, however, an individual can at least partially adapt to such inconsistent cues through either short- [Kassem 1998; Shinn-Cunningham 2000; Shinn-Cunningham et al. 1998a, 1998b; Zahorik 2001] or long- [Hofman et al. 1998] term exposure. The type and degree of inconsistency as well as the length of training determine the final accuracy and consistency with which the subject can localize sounds [Shinn-Cunningham 2000]. The current experiments of short-term adaptation measure how localization bias (mean error) and resolution (precision) change when subjects are exposed to auditory cue rearrangements simpler than those previously investigated. These results, combined with those of earlier experiments, suggest that there is plasticity at many different levels of the spatial auditory processing pathway with different time scales governing the plasticity at different levels of the system. This view of spatial auditory plasticity has important implications for the design of spatial auditory displays.