Speaker Diarization

Speaker Diarization is the task of segmenting and co-indexing audio recordings by speaker. The way the task is commonly defined, the goal is not to identify known speakers, but to co-index segments that are attributed to the same speaker; in other words, diarization implies finding speaker boundaries and grouping segments that belong to the same speaker, and, as a by-product, determining the number of distinct speakers. In combination with speech recognition, diarization enables speaker-attributed speech-to-text transcription.

Source: Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 276–300 of 328 papers

Title	Date	Tasks	Status
Robust speaker recognition using unsupervised adversarial invariance	Nov 3, 2019	speaker-diarizationSpeaker Diarization	CodeCode Available
Meta-learning for robust child-adult classification from speech	Oct 28, 2019	ClassificationMeta-Learning	—Unverified
Speaker diarization using latent space clustering in generative adversarial network	Oct 24, 2019	ClusteringDiagnostic	—Unverified
Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm	Oct 24, 2019	Clusteringspeaker-diarization	—Unverified
Compositional Embeddings: Joint Perception and Comparison of Class Label Sets	Sep 25, 2019	object-detectionObject Detection	—Unverified
Simultaneous Speech Recognition and Speaker Diarization for Monaural Dialogue Recordings with Target-Speaker Acoustic Models	Sep 17, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
End-to-End Neural Speaker Diarization with Permutation-Free Objectives	Sep 12, 2019	ClusteringDomain Adaptation	—Unverified
LSTM based Similarity Measurement with Spectral Clustering for Speaker Diarization	Jul 23, 2019	Change DetectionClustering	CodeCode Available
Toeplitz Inverse Covariance based Robust Speaker Clustering for Naturalistic Audio Streams	Jul 12, 2019	Clusteringspeaker-diarization	—Unverified
Joint Speech Recognition and Speaker Diarization via Sequence Transduction	Jul 9, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions	Jul 1, 2019	speaker-diarizationSpeaker Diarization	CodeCode Available
Large-Scale Speaker Diarization of Radio Broadcast Archives	Jun 19, 2019	speaker-diarizationSpeaker Diarization	—Unverified
The Second DIHARD Diarization Challenge: Dataset, task, and baselines	Jun 18, 2019	Action DetectionActivity Detection	CodeCode Available
UWB-NTIS Speaker Diarization System for the DIHARD II 2019 Challenge	May 27, 2019	Clusteringspeaker-diarization	—Unverified
Meeting Transcription Using Virtual Microphone Arrays	May 3, 2019	speaker-diarizationSpeaker Diarization	—Unverified
Latent Class Model with Application to Speaker Diarization	Apr 25, 2019	modelspeaker-diarization	—Unverified
All-neural online source separation, counting, and diarization for meeting analysis	Feb 21, 2019	AllAutomatic Speech Recognition	—Unverified
Constrained speaker diarization of TV series based on visual patterns	Dec 18, 2018	Clusteringspeaker-diarization	—Unverified
Audiovisual speaker diarization of TV series	Dec 18, 2018	speaker-diarizationSpeaker Diarization	—Unverified
Détection de locuteurs dans les séries TV	Dec 18, 2018	Clusteringspeaker-diarization	—Unverified
Speaker Diarization With Lexical Information	Nov 27, 2018	Clusteringspeaker-diarization	—Unverified
Designing an Effective Metric Learning Pipeline for Speaker Diarization	Nov 1, 2018	Metric Learningspeaker-diarization	—Unverified
CountNet: Estimating the Number of Concurrent Speakers Using Supervised Learning Speaker Count Estimation	Oct 28, 2018	blind source separationspeaker-diarization	CodeCode Available
Semi-supervised acoustic model training for speech with code-switching	Oct 23, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Fully Supervised Speaker Diarization	Oct 10, 2018	Clusteringspeaker-diarization	CodeCode Available

Show:10 25 50

← PrevPage 12 of 14Next →

All datasets CALLHOME NIST-SRE 2000 AMI Lapel AMI MixHeadset CH109 DIHARD ETAPE AMI CALLHOME-109 AliMeeting DIHARD II Hub5'00 CallHome

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	COS+NJW-SC (Oracle SAD)	DER(%)	24.05	—	Unverified
2	EEND	DER(%)	23.07	—	Unverified
3	COS+AHC (Oracle SAD)	DER(%)	21.13	—	Unverified
4	SA-EEND (2-spk, no-adapt)	DER(%)	12.66	—	Unverified
5	EEND-OLA	DER(%)	12.57	—	Unverified
6	SA-EEND (2-spk, adapted)	DER(%)	10.76	—	Unverified
7	TOLD	DER(%)	10.14	—	Unverified
8	COS+B-SC (Oracle SAD)	DER(ig olp)	8.78	—	Unverified
9	PLDA+AHC (Oracle SAD)	DER(ig olp)	8.39	—	Unverified
10	COS+NME-SC (Oracle SAD)	DER(ig olp)	7.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	x-vector (PLDA + AHC)	DER(%)	8.39	—	Unverified
2	TitaNet-L (NME-SC)	DER(%)	6.73	—	Unverified
3	TitaNet-M (NME-SC)	DER(%)	6.47	—	Unverified
4	TitaNet-S (NME-SC)	DER(%)	6.37	—	Unverified
5	x-vector (MCGAN)	DER(%)	5.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ECAPA (SC)	DER(%)	2.36	—	Unverified
2	TitaNet-L (NME-SC)	DER(%)	2.03	—	Unverified
3	TitaNet-S (NME-SC)	DER(%)	2	—	Unverified
4	TitaNet-M (NME-SC)	DER(%)	1.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TitaNet-S (NME-SC)	DER(%)	2.22	—	Unverified
2	TitaNet-M (NME-SC)	DER(%)	1.79	—	Unverified
3	ECAPA (SC)	DER(%)	1.78	—	Unverified
4	TitaNet-L (NME-SC)	DER(%)	1.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	x-vector (PLDA + AHC)	DER(%)	9.72	—	Unverified
2	TitaNet-L (NME-SC)	DER(%)	1.19	—	Unverified
3	TitaNet-M (NME-SC)	DER(%)	1.13	—	Unverified
4	TitaNet-S (NME-SC)	DER(%)	1.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline (the best result in the literature as of Oct.2019)	DER(%)	11.2	—	Unverified
2	pyannote (MFCC)	DER(%)	10.5	—	Unverified
3	pyannote (waveform)	DER(%)	9.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline	DER(%)	7.7	—	Unverified
2	pyannote (MFCC)	DER(%)	5.6	—	Unverified
3	pyannote (waveform)	DER(%)	4.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	pyannote (MFCC)	DER(%)	6.3	—	Unverified
2	pyannote (waveform)	DER(%)	6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	d-vector + spectral	DER(%)	12.54	—	Unverified
2	titanet-s	DER(%)	1.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SOND	DER(%)	4.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UIS-RNN-SML	DER(%)	27.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UIS-RNN	V	10.6	—	Unverified