A study on recognizing distorted speech over local distributed transducer networks

In a collaborative scenario, a multiplicity of portable devices may constitute a network of distributed microphones, without a clearly defined geometric configuration or synchronization that can be taken advantage of for traditional microphone array processing to enhance the acquired signal. This application scenario represents a severe, but interesting challenge for automatic speech recognition systems. In this paper, we investigate a variety of robust speech recognition techniques with a focus on the distributed transducer scenario. We also report some important study results that lead to new thinking in the design of robust speech recognition for broadened applications. Two issues that are inherent to distributed transducer networks are specially investigated. First, we study the effect of the sampling rate skew of microphones to the system performance; second, we explore the possibility of combining recognition hypotheses from multiple transducer channels for improved recognition accuracy.