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 151–175 of 328 papers

Title	Date	Tasks	Status	Hype
Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimation	Oct 24, 2022	Action DetectionActivity Detection	CodeCode Available	1
Mutual Learning of Single- and Multi-Channel End-to-End Neural Diarization	Oct 7, 2022	Knowledge Distillationspeaker-diarization	—Unverified	0
Spatial-aware Speaker Diarization for Multi-channel Multi-party Meeting	Sep 24, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarization	Aug 27, 2022	Action DetectionActivity Detection	—Unverified	0
The Conversational Short-phrase Speaker Diarization (CSSD) Task: Dataset, Evaluation Metric and Baselines	Aug 17, 2022	Machine Translationspeaker-diarization	CodeCode Available	1
Chronological Self-Training for Real-Time Speaker Diarization	Aug 5, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Utterance-by-utterance overlap-aware neural diarization with Graph-PIT	Jul 28, 2022	ClusteringSegmentation	CodeCode Available	1
Unsupervised Speaker Diarization that is Agnostic to Language, Overlap-Aware, and Tuning Free	Jul 25, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Online Target Speaker Voice Activity Detection for Speaker Diarization	Jul 13, 2022	Action DetectionActivity Detection	—Unverified	0
Speaker Diarization and Identification from Single-Channel Classroom Audio Recording Using Virtual Microphones	Jul 1, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Interrelate Training and Searching: A Unified Online Clustering Framework for Speaker Diarization	Jun 28, 2022	ClusteringOnline Clustering	—Unverified	0
Simultaneous Speech Extraction for Multiple Target Speakers under the Meeting Scenarios	Jun 17, 2022	Action DetectionActivity Detection	—Unverified	0
Audio-video fusion strategies for active speaker detection in meetings	Jun 9, 2022	Active Speaker DetectionManagement	—Unverified	0
Online Neural Diarization of Unlimited Numbers of Speakers Using Global and Local Attractors	Jun 6, 2022	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	—Unverified	0
A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification.	Jun 1, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Bazinga! A Dataset for Multi-Party Dialogues Structuring	Jun 1, 2022	Entity LinkingPunctuation Restoration	—Unverified	0
PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit	May 20, 2022	AllAutomatic Speech Recognition (ASR)	CodeCode Available	6
Bi-LSTM Scoring Based Similarity Measurement with Agglomerative Hierarchical Clustering (AHC) for Speaker Diarization	May 19, 2022	Clusteringspeaker-diarization	—Unverified	0
Reformulating Speaker Diarization as Community Detection With Emphasis On Topological Structure	Apr 26, 2022	ClusteringCommunity Detection	—Unverified	0
Improving the Naturalness of Simulated Conversations for End-to-End Neural Diarization	Apr 24, 2022	speaker-diarizationSpeaker Diarization	CodeCode Available	1
Self-supervised Speaker Diarization	Apr 8, 2022	speaker-diarizationSpeaker Diarization	—Unverified	0
Low-Latency Speech Separation Guided Diarization for Telephone Conversations	Apr 5, 2022	Action DetectionActivity Detection	CodeCode Available	1
From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization	Apr 2, 2022	speaker-diarizationSpeaker Diarization	CodeCode Available	1
Multimodal Clustering with Role Induced Constraints for Speaker Diarization	Apr 1, 2022	Clusteringspeaker-diarization	—Unverified	0
EEND-SS: Joint End-to-End Neural Speaker Diarization and Speech Separation for Flexible Number of Speakers	Mar 31, 2022	Decoderspeaker-diarization	—Unverified	0

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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