Role Specific Lattice Rescoring for Speaker Role Recognition from Speech Recognition Outputs

Nikolaos Flemotomos; Panayiotis G. Georgiou; David C. Atkins; Shrikanth S. Narayanan

ICASSP 2019accepted0 citations

Role Specific Lattice Rescoring for Speaker Role Recognition from Speech Recognition Outputs

Nikolaos Flemotomos, Panayiotis G. Georgiou, David C. Atkins, Shrikanth S. Narayanan

Abstract

The language patterns followed by different speakers who play specific roles in conversational interactions provide valuable cues for the task of Speaker Role Recognition (SRR). Given the speech signal, existing algorithms typically try to find such patterns in the output of an Automatic Speech Recognition (ASR) system. In this work we propose an alternative way of revealing role-specific linguistic characteristics, by making use of role-specific ASR outputs, which are built by suitably rescoring the lattice produced after a first pass of ASR decoding. That way, we avoid pruning the lattice too early, eliminating the potential risk of information loss.

BibTeX

@inproceedings{icassp2019_rolespecificlatt,
  title = {Role Specific Lattice Rescoring for Speaker Role Recognition from Speech Recognition Outputs},
  author = {Nikolaos Flemotomos and Panayiotis G. Georgiou and David C. Atkins and Shrikanth S. Narayanan},
  booktitle = {ICASSP 2019},
  year = {2019}
}