  When it comes to authentication in speaker verification systems, not all
utterances are created equal. It is essential to estimate the quality of test
utterances in order to account for varying acoustic conditions. In addition to
the net-speech duration of an utterance, it is observed in this paper that
phonetic richness is also a key indicator of utterance quality, playing a
significant role in accurate speaker verification. Several phonetic histogram
based formulations of phonetic richness are explored using transcripts obtained
from an automatic speaker recognition system. The proposed phonetic richness
measure is found to be positively correlated with voice authentication scores
across evaluation benchmarks. Additionally, the proposed measure in combination
with net speech helps in calibrating the speaker verification scores, obtaining
a relative EER improvement of 5.8% on the Voxceleb1 evaluation protocol. The
proposed phonetic richness based calibration provides higher benefit for short
utterances with repeated words.
