Abstract: A method and apparatus for identifying a speaker within a captured audio signal from a collection of known speakers. The method and apparatus receive or generate voice representations for each known speakers and tag the representations according to meta data related to the known speaker or to the voice. The representations are grouped into one or more groups according to the indices. When a voice to be recognized is introduced, characteristics are determined according to which the groups are prioritized, so that the representations participating only in part of the groups are matched against the voice to be identified, thus reducing identification time and improving the statistical significance.

Abstract: A method for spotting an interaction in which a target speaker associated with a current index or current interaction speaks, the method comprising: receiving an interaction and an index associated with the interaction, the index associated with additional data; receiving the current interaction or current index associated with the target speaker; obtaining current data associated with the current interaction or current index; filtering the index using the additional data, in accordance with the current data associated with the current interaction or current index, and obtaining a matching index; and comparing the current index or a representation of the current interaction with the matching index to obtain a target speaker index.

Abstract: A method and apparatus for identifying a speaker within a captured audio signal from a collection of known speakers. The method and apparatus receive or generate voice representations for each known speakers and tag the representations according to meta data related to the known speaker or to the voice. The representations are grouped into one or more groups according to the indices. When a voice to be recognized is introduced, characteristics are determined according to which the groups are prioritized, so that the representations participating only in part of the groups are matched against the o voice to be identified, thus reducing identification time and improving the statistical significance.