Title
Role Specific Lattice Rescoring For Speaker Role Recognition From Speech Recognition Outputs
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.
Year
DOI
Venue
2019
10.1109/icassp.2019.8683900
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
speaker role recognition, speech recognition, language model, lattice rescoring
Information loss,Lattice (order),Computer science,Speech recognition,Pattern language,Decoding methods,Language model
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Flemotomos Nikolaos112.05
Georgiou Panayiotis242855.79
David Atkins35512.28
Narayanan Shrikanth45558439.23