Speech segregation, or the cocktail party problem, has proven to be extremely challenging. This presentation describes a computational auditory scene analysis (CASA) approach to the cocktail party problem. This approach performs auditory segmentation and grouping in a two-dimensional time-frequency representation that encodes proximity in frequency and time, periodicity, amplitude modulation, a...

We introduce context-aware scalable authentication (CASA) as a way of balancing security and usability for authentication. Our core idea is to combine a number of passive factors for authentication (e.g., a user’s current location) with appropriate active factors. In this paper, we provide a probabilistic framework for dynamically selecting an active authentication scheme that satisfies a secur...

Robustness is one of the most important topics for automatic speech recognition (ASR) in practical applications. Monaural speech separation based on computational auditory scene analysis (CASA) offers a solution to this problem. In this paper, a novel system is presented to separate the monaural speech of two talkers. Gaussian mixture models (GMMs) and vector quantizers (VQs) are used to learn ...

The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is embarking on a paradigm of network of small radars to sample the atmosphere at high resolution. A fundamental physical limit imposed by transmission from single radar is the problem of decreasing resolution as a function of range. In addition the lowest coverage altitude increases with range due to earth curvature. As an ...

1 INTRODUCTION In this chapter I briefly review the history and the future of computational auditory scene analysis (CASA). Auditory scene analysis describes the process we use to understand the world around us. Our two ears hear a cacophony of sounds and understand that the periodic tic-toc comes from a clock, the singing voice comes from a radio and the steady hum is coming from the refrigera...