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.
@article{arxiv.1904.04240,
title = {MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation},
author = {Suwon Shon and Najim Dehak and Douglas Reynolds and James Glass},
journal= {arXiv preprint arXiv:1904.04240},
year = {2019}
}
Comments
http://mce.csail.mit.edu . arXiv admin note: text overlap with arXiv:1807.06663