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

Showing 226250 of 328 papers

TitleStatusHype
Unsupervised Speaker Diarization that is Agnostic to Language, Overlap-Aware, and Tuning Free0
Using Active Speaker Faces for Diarization in TV shows0
Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones0
UWB-NTIS Speaker Diarization System for the DIHARD II 2019 Challenge0
VOXLINGUA107: A DATASET FOR SPOKEN LANGUAGE RECOGNITION0
VoxRAG: A Step Toward Transcription-Free RAG Systems in Spoken Question Answering0
Weakly Supervised Training of Speaker Identification Models0
An approach to optimize inference of the DIART speaker diarization pipeline0
SCDiar: a streaming diarization system based on speaker change detection and speech recognition0
SC-SOT: Conditioning the Decoder on Diarized Speaker Information for End-to-End Overlapped Speech Recognition0
SEAL: Speaker Error Correction using Acoustic-conditioned Large Language Models0
Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models0
Segmentation et Regroupement en Locuteurs d'une collection de documents audio (Cross-show speaker diarization) [in French]0
Self-supervised learning for audio-visual speaker diarization0
Self-supervised Speaker Diarization0
Semi-supervised acoustic modelling for five-lingual code-switched ASR using automatically-segmented soap opera speech0
Semi-supervised Acoustic Modelling for Five-lingual Code-switched ASR using Automatically-segmented Soap Opera Speech0
Semi-supervised acoustic model training for speech with code-switching0
Semi-supervised multi-channel speaker diarization with cross-channel attention0
SeniorTalk: A Chinese Conversation Dataset with Rich Annotations for Super-Aged Seniors0
Separation Guided Speaker Diarization in Realistic Mismatched Conditions0
Sequence-to-Sequence Neural Diarization with Automatic Speaker Detection and Representation0
Simultaneous Speech Extraction for Multiple Target Speakers under the Meeting Scenarios0
Simultaneous Speech Recognition and Speaker Diarization for Monaural Dialogue Recordings with Target-Speaker Acoustic Models0
Sortformer: Seamless Integration of Speaker Diarization and ASR by Bridging Timestamps and Tokens0
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Benchmark Results

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