mlsanityData to 14 Oct 2026

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

arXiv 1904.04240 ↗First posted 7 Apr 2019eess.AS cs.SDcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2019.

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Citing papers per year: 2021: 1; 2022: 0; 2023: 2.

3 papers.