pith. sign in

arxiv: 1904.04240 · v1 · pith:RBCDIUGCnew · submitted 2019-04-07 · 📡 eess.AS · cs.SD

MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation

classification 📡 eess.AS cs.SD
keywords speakerblacklistedchallengemulti-targetconversationsdetectionspokenwhether
0
0 comments X
read the original abstract

The Multi-target Challenge aims to assess how well current speech technology is able to determine whether or not a recorded utterance was spoken by one of a large number of blacklisted speakers. It is a form of multi-target speaker detection based on real-world telephone conversations. Data recordings are generated from call center customer-agent conversations. The task is to measure how accurately one can detect 1) whether a test recording is spoken by a blacklisted speaker, and 2) which specific blacklisted speaker was talking. This paper outlines the challenge and provides its baselines, results, and discussions.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.