2016 · 39 citations · 13 references
EngineeringMachine LearningSitw DatabaseWild Acoustic ConditionsVoice EvaluationSpeech RecognitionNatural Language ProcessingOpen Source MediaData SciencePattern RecognitionSpeaker IdentificationSpeaker DiarizationRobust Speech RecognitionAutomatic RecognitionAcoustic AnalysisHealth SciencesComputer ScienceSpeech CommunicationVoiceMulti-speaker Speech RecognitionSpeech ProcessingSpeech PerceptionSpeaker Recognition
The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8 sessions per speaker. The recordings contain unconstrained or wild acoustic conditions, rarely found in large speaker recognition datasets, and multi-speaker recordings for both speaker enrollment and verification. This article provides details of the SITW speaker recognition challenge and analysis of evaluation results. There were 25 international teams involved in the challenge of which 11 teams participated in an evaluation track. Teams were tasked with applying existing and novel speaker recognition algorithms to the challenges associated with the real world conditions of SITW. We provide an analysis of some of the top performing systems submitted during the evaluation and provide future research directions. Copyright ©2016 ISCA.
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