Linguistically Aided Speaker Diarization Using Speaker Role Information

Speaker diarization relies on the assumption that speech segments corresponding to a particular speaker are concentrated in a specific region of the speaker space; a region which represents that speaker's identity. These identities are not known a priori, so a clustering algorithm is typically employed, which is traditionally based solely on audio. Under noisy conditions, however, such an approach poses the risk of generating unreliable speaker...