SOTAVerified

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

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Showing 51–75 of 328 papers

TitleStatusHype
TalTech-IRIT-LIS Speaker and Language Diarization Systems for DISPLACE 2024—0
psifx -- Psychological and Social Interactions Feature Extraction Package—0
A Benchmark for Multi-speaker Anonymization—0
Systematic Evaluation of Online Speaker Diarization Systems Regarding their Latency—0
The USTC-NERCSLIP Systems for The ICMC-ASR Challenge—0
Towards Unsupervised Speaker Diarization System for Multilingual Telephone Calls Using Pre-trained Whisper Model and Mixture of Sparse Autoencoders—0
Audio-Visual Approach For Multimodal Concurrent Speaker Detection—0
Leveraging Speaker Embeddings in End-to-End Neural Diarization for Two-Speaker Scenarios—0
From Modular to End-to-End Speaker Diarization—0
Speakers Unembedded: Embedding-free Approach to Long-form Neural Diarization—0
AG-LSEC: Audio Grounded Lexical Speaker Error Correction—0
Investigating Confidence Estimation Measures for Speaker Diarization—0
System Description for the Displace Speaker Diarization Challenge 2023—0
A Review of Common Online Speaker Diarization Methods—0
Joint vs Sequential Speaker-Role Detection and Automatic Speech Recognition for Air-traffic Control—0
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences—0
The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments—0
Exploring Spoken Language Identification Strategies for Automatic Transcription of Multilingual Broadcast and Institutional Speech—0
Exploring Speech Foundation Models for Speaker Diarization in Child-Adult Dyadic InteractionsCode1
Neural Blind Source Separation and Diarization for Distant Speech Recognition—0
Target Speech Diarization with Multimodal Prompts—0
LLM-based speaker diarization correction: A generalizable approachCode1
ASoBO: Attentive Beamformer Selection for Distant Speaker Diarization in Meetings—0
Speaker Embeddings With Weakly Supervised Voice Activity Detection For Efficient Speaker Diarization—0
A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COS+NJW-SC (Oracle SAD)DER(%)24.05—Unverified
2EENDDER(%)23.07—Unverified
3COS+AHC (Oracle SAD)DER(%)21.13—Unverified
4SA-EEND (2-spk, no-adapt)DER(%)12.66—Unverified
5EEND-OLADER(%)12.57—Unverified
6SA-EEND (2-spk, adapted)DER(%)10.76—Unverified
7TOLDDER(%)10.14—Unverified
8COS+B-SC (Oracle SAD)DER(ig olp)8.78—Unverified
9PLDA+AHC (Oracle SAD)DER(ig olp)8.39—Unverified
10COS+NME-SC (Oracle SAD)DER(ig olp)7.29—Unverified
#ModelMetricClaimedVerifiedStatus
1x-vector (PLDA + AHC)DER(%)8.39—Unverified
2TitaNet-L (NME-SC)DER(%)6.73—Unverified
3TitaNet-M (NME-SC)DER(%)6.47—Unverified
4TitaNet-S (NME-SC)DER(%)6.37—Unverified
5x-vector (MCGAN)DER(%)5.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ECAPA (SC)DER(%)2.36—Unverified
2TitaNet-L (NME-SC)DER(%)2.03—Unverified
3TitaNet-S (NME-SC)DER(%)2—Unverified
4TitaNet-M (NME-SC)DER(%)1.99—Unverified
#ModelMetricClaimedVerifiedStatus
1TitaNet-S (NME-SC)DER(%)2.22—Unverified
2TitaNet-M (NME-SC)DER(%)1.79—Unverified
3ECAPA (SC)DER(%)1.78—Unverified
4TitaNet-L (NME-SC)DER(%)1.73—Unverified
#ModelMetricClaimedVerifiedStatus
1x-vector (PLDA + AHC)DER(%)9.72—Unverified
2TitaNet-L (NME-SC)DER(%)1.19—Unverified
3TitaNet-M (NME-SC)DER(%)1.13—Unverified
4TitaNet-S (NME-SC)DER(%)1.11—Unverified
#ModelMetricClaimedVerifiedStatus
1Baseline (the best result in the literature as of Oct.2019)DER(%)11.2—Unverified
2pyannote (MFCC)DER(%)10.5—Unverified
3pyannote (waveform)DER(%)9.9—Unverified
#ModelMetricClaimedVerifiedStatus
1BaselineDER(%)7.7—Unverified
2pyannote (MFCC)DER(%)5.6—Unverified
3pyannote (waveform)DER(%)4.9—Unverified
#ModelMetricClaimedVerifiedStatus
1pyannote (MFCC)DER(%)6.3—Unverified
2pyannote (waveform)DER(%)6—Unverified
#ModelMetricClaimedVerifiedStatus
1d-vector + spectralDER(%)12.54—Unverified
2titanet-sDER(%)1.11—Unverified
#ModelMetricClaimedVerifiedStatus
1SONDDER(%)4.46—Unverified
#ModelMetricClaimedVerifiedStatus
1UIS-RNN-SMLDER(%)27.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UIS-RNNV10.6—Unverified