Accuracy of recognition memory for common sounds

Supervised Feature Extraction of Face Images for Improvement of Recognition Accuracy

Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...

Accounts of the confidence-accuracy relation in recognition memory.

Confidence and accuracy, while often considered to tap the same memory representation, are often found to be only weakly correlated (e.g., Bothwell, Deffenbacher, & Brigham, 1987; Deffenbacher, 1980). There are at least two possible (nonexclusive) reasons for this weak relation. First, it may be simply due to noise of one sort or another; that is, it may come about because of both within- and b...

Automatic Recognition of Bioacoustic Sounds

Modelling Non-verbal Sounds for Speech Recognition

I N T R O D U C T I O N Recent experiments performed by two groups of researchers at CMU have gathered data on subjects using speech recognizers in office-like environments (Rudnicky, et al., 1989, Stern & Acero, 1989). These experiments are presented by the authors in these proceedings. Among other things, they show that non-verbal events (non-stationary noises) do create serious problems for ...

Organization of sequential sounds in auditory memory.

A repeating five-tone pattern was presented at several stimulus rates (200, 400, 600, and 800 ms onset-to-onset) to determine at what temporal proximity the five-tone repeating unit would be represented in memory. The mismatch negativity component of event-related brain potentials was used to index how the sounds were organized in memory when participants had no task with the sounds. Only at th...