Speech babble: Analysis and modeling for speech systems

Abstract

Speech babble represents the most challenging noise interference in all speech systems, yet no research has been performed at a systematic level to model the underlying structure. For the first time, this study establishes a working foundation for the analysis and modeling of babble speech. We first address the underlying model for multiple speaker babble speech - considering the number of conversations versus the number of speakers. Next, based on this model, we develop an algorithm to detect the range of speakers within an unknown babble speech sequence. Evaluation is performed using 110 hours of data from the SWITCHBOARD corpus. The number of simultaneous conversations ranges from 1-9, or 1 to 18 subjects speaking. A speaker conversation stream detection rate in excess of 80% is achieved with a speaker window size of plusmn 1 speaker. This study is the first in developing an effective speaker babble model to contribute to robust speech systems.