Automatic Speaker Recognition Using Gaussian Mixture Speaker Models

• Speech conveys several levels of information. On a primary level, speech conveys the words or message being spoken, but on a secondary level, speech also reveals information about the speaker. The Speech Systems Technology group at Lincoln Laboratory has developed and experimented with approaches for automatically recognizing the words being spoken, the language being spoken, and the topic of a conversation. In this article we present an overview of our research efforts in a fourth area-automatic speaker recognition. We base our approach on a statistical speaker-modeling technique that represents the underlying characteristic sounds of a person's voice. Using these models, we build speaker recognizers that are computationally inexpensive and capable of recognizing a speaker regardless ofwhat is being said. Performance of the systems is evaluated for a wide range of speech quality; from clean speech to telephone speech, by using several standard speech corpora.