Speaker recognition based on deep learning: An overview

Speaker Diarization with Enhancing Speech for the First DIHARD Challenge

Sun, L., Du, J., Jiang, C., Zhang, X., He, S., Yin, B., & Lee, C. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1742 · Cited by 37

Channel Adversarial Training for Cross-channel Text-independent Speaker Recognition

Fang, X., Zou, L., Li, J., Sun, L., & Ling, Z.-H. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682327 · Cited by 37

The INTERSPEECH 2020 Far-Field Speaker Verification Challenge

Qin, X., Li, M., Bu, H., Rao, W., Das, R. K., Narayanan, S. S., & Li, H. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1249 · Cited by 37

Who Said That?: Audio-Visual Speaker Diarisation of Real-World Meetings

Chung, J. S., Lee, B., & Han, I. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-3116 · Cited by 36

Few Shot Speaker Recognition using Deep Neural NetworksPreprint

Anand, P., Singh, A. K., Srivastava, S., & Lall, B. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.08775 · Cited by 36

Multimodal Speaker Segmentation and Diarization Using Lexical and Acoustic Cues via Sequence to Sequence Neural Networks

Park, T., & Georgiou, P. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1364 · Cited by 35

Adapting End-to-end Neural Speaker Verification to New Languages and Recording Conditions with Adversarial Training

Bhattacharya, G., Alam, J., & Kenny, P. J. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682611 · Cited by 35

Discriminative Neural Embedding Learning for Short-Duration Text-Independent Speaker Verification

Wang, S., Huang, Z., Qian, Y., & Yu, K. (2019) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2019.2928128 · Cited by 35

The JHU Speaker Recognition System for the VOiCES 2019 Challenge

Snyder, D., Villalba, J., Chen, N., Povey, D., Sell, G., Dehak, N., & Khudanpur, S. P. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2979 · Cited by 35

Evaluating Automatic Speaker Recognition systems: An overview of the NIST Speaker Recognition Evaluations (1996-2014)

González-Rodríguez, J. (2014) · Loquens · doi:10.3989/loquens.2014.007 · Cited by 35

Speaker Characterization Using TDNN-LSTM Based Speaker Embedding

Chen, C.-P., Zhang, S.-Y., Yeh, C.-T., Wang, J., Wang, T., & Huang, C.-L. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683185 · Cited by 35

Speech overlap detection in a two-pass speaker diarization system

Huijbregts, M., van Leeuwen, D. A., & de Jong, F. M. G. (2009) · Interspeech (USB) · doi:10.21437/interspeech.2009-326 · Cited by 34

Speaker Verification Using Deep Neural Networks: A Review

Irum, A., & Salman, A. (2019) · International Journal of Machine Learning and Computing · doi:10.18178/ijmlc.2019.9.1.760 · Cited by 33

Neural Speech Turn Segmentation and Affinity Propagation for Speaker Diarization

Yin, R., Bredin, H., & Barras, C. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1750 · Cited by 33

Feature Enhancement with Deep Feature Losses for Speaker Verification

Kataria, S., Nidadavolu, P. S., Villalba, J., Chen, N., García-Perera, P., & Dehak, N. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053110 · Cited by 33

On Robustness of Unsupervised Domain Adaptation for Speaker Recognition

Bousquet, P.-M., & Rouvier, M. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1524 · Cited by 32

Improving Deep CNN Networks with Long Temporal Context for Text-Independent Speaker Verification

Zhao, Y. H., Zhou, T., Chen, Z., & Wu, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053767 · Cited by 32

Partial AUC Optimization Based Deep Speaker Embeddings with Class-Center Learning for Text-Independent Speaker Verification

Bai, Z., Zhang, X.-L., & Chen, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053674 · Cited by 32

Modelling speaker and channel variability using deep neural networks for robust speaker verification

Bhattacharya, G., Alam, J., Kenn, P., & Gupta, V. (2016) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt.2016.7846264 · Cited by 31

Far-Field End-to-End Text-Dependent Speaker Verification Based on Mixed Training Data with Transfer Learning and Enrollment Data Augmentation

Qin, X., Cai, D., & Li, M. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1542 · Cited by 31

Cycle-GANs for Domain Adaptation of Acoustic Features for Speaker Recognition

Nidadavolu, P. S., Villalba, J., & Dehak, N. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683055 · Cited by 30

Multilayer bootstrap networks

Zhang, X.-L. (2018) · Neural Networks · doi:10.1016/j.neunet.2018.03.005 · Cited by 29

Self-Supervised Learning for Audio-Visual Speaker Diarization

Ding, Y., Xu, Y., Zhang, S.-X., Cong, Y., & Wang, L. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054376 · Cited by 29

Wav2Spk: A Simple DNN Architecture for Learning Speaker Embeddings from Waveforms

Lin, W., & Mak, M. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1287 · Cited by 29

Deep bottleneck features for i-vector based text-independent speaker verification

Ghalehjegh, S. H., & Rose, R. C. (2015) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru.2015.7404844 · Cited by 28

AM-MobileNet1D: A Portable Model for Speaker Recognition

Nunes, J. A. C., Macêdo, D., & Zanchettin, C. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9207519 · Cited by 28

BERTphone: Phonetically-aware Encoder Representations for Utterance-level Speaker and Language Recognition

Ling, S., Salazar, J., Liu, Y., & Kirchhoff, K. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-2 · Cited by 28

Deep neural network based posteriors for text-dependent speaker verification

Dey, S., Madikeri, S. R., Ferràs, M., & Motlíček, P. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7472639 · Cited by 28

Combination of Cepstral and Phonetically Discriminative Features for Speaker Verification

Sarkar, A. K., Do, C.-T., Le, V.-B., & Barras, C. (2014) · IEEE Signal Processing Letters · doi:10.1109/lsp.2014.2323432 · Cited by 28

Supervised Online Diarization with Sample Mean Loss for Multi-Domain Data

Fini, E., & Brutti, A. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053477 · Cited by 28

Speaker Diarization with Session-Level Speaker Embedding Refinement Using Graph Neural Networks

Wang, J., Xiao, X., Wu, J., Ramamurthy, R., Rudzicz, F., & Brudno, M. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054176 · Cited by 28

Text-dependent speaker verification based on i-vectors, Neural Networks and Hidden Markov Models

Zeinali, H., Sameti, H., Burget, L., & Černocký, J. (2017) · Computer Speech & Language · doi:10.1016/j.csl.2017.04.005 · Cited by 27

Frame-Level Phoneme-Invariant Speaker Embedding for Text-Independent Speaker Recognition on Extremely Short Utterances

Tawara, N., Ogawa, A., Iwata, T., Delcroix, M., & Ogawa, T. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053871 · Cited by 27

Deep Neural Networks and Hidden Markov Models in i-vector-based Text-Dependent Speaker Verification

Zeinali, H., Burget, L., Sameti, H., Glembek, O., & Plchot, O. (2016) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2016-4 · Cited by 27

Deep neural network based i-vector mapping for speaker verification using short utterances

Guo, J., Xu, N., Qian, K., Shi, Y., Xu, K., Wu, Y., & Alwan, A. A. (2018) · Speech Communication · doi:10.1016/j.specom.2018.10.004 · Cited by 27

Spatial Pyramid Encoding with Convex Length Normalization for Text-Independent Speaker Verification

Jung, Y., Kim, Y., Lim, H., Choi, Y., & Kim, H. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2177 · Cited by 27

Shortcut Connections Based Deep Speaker Embeddings for End-to-End Speaker Verification System

Seo, S., Rim, D. J., Lim, M., Lee, D., Park, H.-S., Oh, J.-S., Kim, C., & Kim, J. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2195 · Cited by 27

Dynamic Margin Softmax Loss for Speaker Verification

Zhou, D., Wang, L., Lee, K. A., Wu, Y., Liu, M., Dang, J., & Wei, J. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1106 · Cited by 27

A Robust Text-independent Speaker Verification Method Based on Speech Separation and Deep Speaker

Zhao, F., Li, H., & Zhang, X. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683762 · Cited by 26

Dereverberation and Beamforming in Far-Field Speaker Recognition

Mošner, L., Matějka, P., Novotný, O., & Černocký, J. (2018) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2018.8462365 · Cited by 26

An Improved Deep Embedding Learning Method for Short Duration Speaker Verification

Gao, Z., Song, Y., McLoughlin, I. V., Guo, W., & Dai, L.-R. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1515 · Cited by 26

I-vector Transformation Using Conditional Generative Adversarial Networks for Short Utterance Speaker Verification

Zhang, J., Inoue, N., & Shinoda, K. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1680 · Cited by 26

Low-Resource Domain Adaptation for Speaker Recognition Using Cycle-Gans

Nidadavolu, P. S., Kataria, S., Villalba, J., & Dehak, N. (2019) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru46091.2019.9003748 · Cited by 26

Robust Speaker Recognition Using Unsupervised Adversarial Invariance

Peri, R., Pal, M., Jati, A., Somandepalli, K., & Narayanan, S. S. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054601 · Cited by 25

Vector-Based Attentive Pooling for Text-Independent Speaker Verification

Wu, Y., Guo, C., Gao, H., Hou, X., & Xu, J. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1422 · Cited by 25

DNN-Based Amplitude and Phase Feature Enhancement for Noise Robust Speaker Identification

Oo, Z., Kawakami, Y., Wang, L., Nakagawa, S., Xiao, X., & Iwahashi, M. (2016) · Interspeech (USB) · doi:10.21437/interspeech.2016-717 · Cited by 25

Speaker Diarization Using Convolutional Neural Network for Statistics Accumulation Refinement

Zajíc, Z., Hrúz, M., & Müller, L. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-51 · Cited by 25

An Effective Deep Embedding Learning Architecture for Speaker Verification

Jiang, Y., Song, Y., McLoughlin, I. V., Gao, Z., & Dai, L.-R. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1606 · Cited by 25

Deep Learning Based Multi-Channel Speaker Recognition in Noisy and Reverberant Environments

Taherian, H., Wang, Z.-Q., & Wang, D. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1428 · Cited by 25

Gaussian-constrained Training for Speaker Verification

Li, L., Tang, Z., Shi, Y., & Wang, D. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683245 · Cited by 25

i-Vector Transformation Using a Novel Discriminative Denoising Autoencoder for Noise-Robust Speaker Recognition

Mahto, S., Yamamoto, H., & Koshinaka, T. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-731 · Cited by 24

Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification Using CTC-Based Soft VAD and Global Query Attention

Jung, M., Jung, Y., Goo, J., & Kim, H. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1420 · Cited by 24

Linguistically Aided Speaker Diarization Using Speaker Role Information

Flemotomos, N., Georgiou, P., & Narayanan, S. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-17 · Cited by 23

In-Domain and Out-of-Domain Data Augmentation to Improve Children’s Speaker Verification System in Limited Data Scenario

Shahnawazuddin, S., Ahmad, W., Adiga, N., & Kumar, A. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053891 · Cited by 23

A comparison of neural network feature transforms for speaker diarization

Yella, S. H., & Stolcke, A. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-101 · Cited by 22

End-to-End Losses Based on Speaker Basis Vectors and All-Speaker Hard Negative Mining for Speaker Verification

Heo, H.-S., Jung, J.-W., Yang, I.-H., Yoon, S.-H., Shim, H.-J., & Yu, H.-J. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1986 · Cited by 22

Speaker Verification by Partial AUC Optimization With Mahalanobis Distance Metric Learning

Bai, Z., Zhang, X.-L., & Chen, J. (2020) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2020.2990275 · Cited by 22

Mixup Learning Strategies for Text-Independent Speaker Verification

Zhu, Y., Ko, T., & Mak, B. K.-W. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2250 · Cited by 22

Channel Invariant Speaker Embedding Learning with Joint Multi-Task and Adversarial Training

Chen, Z., Wang, S., Qian, Y., & Yu, K. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053905 · Cited by 22

Boundary Discriminative Large Margin Cosine Loss for Text-independent Speaker Verification

Li, R., Li, N., Tuo, D., Yu, M., Su, D., & Yu, D. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682749 · Cited by 21

Speaker Diarization Using Latent Space Clustering in Generative Adversarial Network

Pal, M., Kumar, M., Peri, R., Park, T., Kim, S. H., Lord, C., Bishop, S. L., & Narayanan, S. S. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053952 · Cited by 21

Multi-Channel Training for End-to-End Speaker Recognition Under Reverberant and Noisy Environment

Cai, D., Qin, X., & Li, M. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1437 · Cited by 20

Discriminative Neural Clustering for Speaker DiarisationPreprint

Li, Q., Kreyssig, F., Zhang, C., & Woodland, P. C. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.09703 · Cited by 20

Statistics Pooling Time Delay Neural Network Based on X-Vector for Speaker Verification

Hong, Q.-B., Wu, C., Wang, H., & Huang, C.-L. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054350 · Cited by 19

SNR-Invariant Multitask Deep Neural Networks for Robust Speaker Verification

Yao, Q., & Mak, M. (2018) · IEEE Signal Processing Letters · doi:10.1109/lsp.2018.2870726 · Cited by 19

Speaker segmentation using deep speaker vectors for fast speaker change scenarios

Wang, R., Gu, M., Li, L., Xu, M., & Zheng, T. F. (2017) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2017.7953192 · Cited by 19

Optimization of False Acceptance/Rejection Rates and Decision Threshold for End-to-End Text-Dependent Speaker Verification Systems

Mingote, V., Miguel, A., Ribas, D., Ortega, A., & Lleida, E. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2550 · Cited by 19

Multimodal Speaker Diarization of Real-World Meetings Using D-Vectors With Spatial Features

Kang, W., Roy, B., & Chow, W. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053122 · Cited by 19

Optimizing Bayesian Hmm Based X-Vector Clustering for the Second Dihard Speech Diarization Challenge

Díez, M., Burget, L., Landini, F., Wang, S., & Černocký, H. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053982 · Cited by 18

DNN Based Speaker Embedding Using Content Information for Text-Dependent Speaker Verification

Dey, S., Koshinaka, T., Motlíček, P., & Madikeri, S. R. (2018) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2018.8461389 · Cited by 17

Speaker diarization with i-vectors from DNN senone posteriors

Sell, G., Garcia-Romero, D., & McCree, A. V. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-109 · Cited by 17

Unsupervised Feature Enhancement for Speaker Verification

Nidadavolu, P. S., Kataria, S., Villalba, J., García-Perera, P., & Dehak, N. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053823 · Cited by 17

Channel Adversarial Training for Speaker Verification and Diarization

Luu, C., Bell, P., & Renals, S. J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053323 · Cited by 16

DNN-Based Speaker Clustering for Speaker Diarisation

Milner, R., & Hain, T. (2016) · Interspeech (USB) · doi:10.21437/interspeech.2016-126 · Cited by 16

An End-to-End Text-Independent Speaker Identification System on Short Utterances

Ji, R., Cai, X., & Xu, B. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1058 · Cited by 16

Joint I-Vector with End-to-End System for Short Duration Text-Independent Speaker Verification

Huang, Z., Wang, S., & Qian, Y. (2018) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2018.8462508 · Cited by 16

A Comparative Re-Assessment of Feature Extractors for Deep Speaker Embeddings

Liu, X., Sahidullah, M., & Kinnunen, T. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1765 · Cited by 16

Self-Attentive Similarity Measurement Strategies in Speaker Diarization

Lin, Q., Hou, Y., & Li, M. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-1908 · Cited by 16

Combining Deep Embeddings of Acoustic and Articulatory Features for Speaker Identification

Hong, Q.-B., Wu, C., Wang, H., & Huang, C.-L. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053640 · Cited by 15

Maximum-Likelihood Linear Transformation for Unsupervised Domain Adaptation in Speaker Verification

Misra, A., & Hansen, J. H. L. (2018) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2018.2831460 · Cited by 15

Pre-training of Speaker Embeddings for Low-latency Speaker Change Detection in Broadcast News

Sarı, L., Thomas, S., Hasegawa‐Johnson, M., & Picheny, M. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683612 · Cited by 15

A deep neural network speaker verification system targeting microphone speech

Lei, Y., Ferrer, L., McLaren, M., & Scheffer, N. (2014) · Interspeech (USB) · doi:10.21437/interspeech.2014-171 · Cited by 14

Deeply Fused Speaker Embeddings for Text-Independent Speaker Verification

Bhattacharya, G., Alam, M. J., Gupta, V., & Kenny, P. J. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1688 · Cited by 14

Text-Independent Speaker Verification with Adversarial Learning on Short Utterances

Liu, K., & Zhou, H. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054036 · Cited by 14

Joint Training of Expanded End-to-End DNN for Text-Dependent Speaker Verification

Heo, H.-S., Jung, J.-W., Yang, I.-H., Yoon, S.-H., & Yu, H.-J. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-1050 · Cited by 13

Domain adaptation using maximum likelihood linear transformation for PLDA-based speaker verification

Wang, Q., Yamamoto, H., & Koshinaka, T. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7472651 · Cited by 13

A Generalized Framework for Domain Adaptation of PLDA in Speaker Recognition

Wang, Q., Okabe, K., Lee, K. A., & Koshinaka, T. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054113 · Cited by 13

On the use of DNN Autoencoder for Robust Speaker RecognitionPreprint

Novotný, O., Plchot, O., Matějka, P., & Glembek, O. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.02938 · Cited by 12

End-to-end Text-dependent Speaker Verification Using Novel Distance Measures

Dey, S., Madikeri, S. R., & Motlíček, P. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-2300 · Cited by 11

Deep Speaker Representation Using Orthogonal Decomposition and Recombination for Speaker Verification

Kim, I.-S., Kim, K. H., Kim, J., & Choi, C. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8683332 · Cited by 11

DIHARD II is Still Hard: Experimental Results and Discussions from the DKU-LENOVO Team

Lin, Q., Cai, W., Yang, L., Wang, J., Zhang, J., & Li, M. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-15 · Cited by 11

Evolutionary Algorithm Enhanced Neural Architecture Search for Text-Independent Speaker Verification

Qu, X., Wang, J., & Xiao, J. Z. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-3057 · Cited by 11

Information Maximized Variational Domain Adversarial Learning for Speaker Verification

Tu, Y., Mak, M., & Chien, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053735 · Cited by 11

Toward Better Speaker Embeddings: Automated Collection of Speech Samples From Unknown Distinct Speakers

Pham, T. M., Li, Z., & Whitehill, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053258 · Cited by 11

Compact Speaker Embedding: lrx-Vector

Georges, M., Huang, J., & Bocklet, T. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2106 · Cited by 10

Exploiting sequence information for text-dependent Speaker Verification

Dey, S., Motlíček, P., Madikeri, S. R., & Ferràs, M. (2017) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2017.7953182 · Cited by 10

Bayesian x-vector: Bayesian Neural Network based x-vector System for Speaker Verification

Xu, L., Zhong, J., Yu, J., Hu, S., Wu, X., Liu, X., & Meng, H. M. L. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-51 · Cited by 10

Context and Uncertainty Modeling for Online Speaker Change Detection

Aronowitz, H., & Zhu, W. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053280 · Cited by 10

Multi-Task Discriminative Training of Hybrid DNN-TVM Model for Speaker Verification with Noisy and Far-Field Speech

Jati, A., Peri, R., Pal, M., Park, T., Kumar, N., V, Travadi, R., Georgiou, P., & Narayanan, S. S. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-3010 · Cited by 9

Augmenting short-term cepstral features with long-term discriminative features for speaker verification of telephone data

Do, C.-T., Barras, C., Le, V.-B., & Sarkar, A. K. (2013) · Interspeech (USB) · doi:10.21437/interspeech.2013-415 · Cited by 9

Low-latency speaker spotting with online diarization and detection

Patiño, J. F., Yin, R., Delgado, H., Bredin, H., Komaty, A., Wisniewski, G., Barras, C., Evans, N., & Marcel, S. (2018) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2018-20 · Cited by 9

Angular Margin Centroid Loss for Text-Independent Speaker Recognition

Wei, Y., Du, J., & Liu, H. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2538 · Cited by 9

Online End-to-End Neural Diarization with Speaker-Tracing BufferPreprint

Xue, Y., Horiguchi, S., Fujita, Y., Watanabe, S., & Nagamatsu, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.02616 · Cited by 9

Phone-centric local variability vector for text-constrained speaker verification

Chen, L., Lee, K. A., Ma, B., Guo, W., Li, H., & Dai, L.-R. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-90 · Cited by 8

Dereverberation and Beamforming in Robust Far-Field Speaker Recognition

Mošner, L., Plchot, O., Matějka, P., Novotný, O., & Černocký, J. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-2306 · Cited by 8

An Unsupervised Neural Prediction Framework for Learning Speaker Embeddings Using Recurrent Neural Networks

Jati, A., & Georgiou, P. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1363 · Cited by 8

On Parameter Adaptation in Softmax-Based Cross-Entropy Loss for Improved Convergence Speed and Accuracy in DNN-Based Speaker Recognition

Rybicka, M., & Kowalczyk, K. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2264 · Cited by 8

Exploring robustness of DNN/RNN for extracting speaker baum-welch statistics in mismatched conditions

Zheng, H., Zhang, S., & Liu, W. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-302 · Cited by 7

An Improved Deep Neural Network for Modeling Speaker Characteristics at Different Temporal Scales

Gu, B., Guo, W., Dai, L.-R., & Du, J. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054151 · Cited by 7

The FFSVC 2020 Evaluation PlanPreprint

Qin, X., Li, M., Bu, H., Das, R. K., Rao, W., Narayanan, S. S., & Li, H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.00387 · Cited by 7

Universal Background Sparse Coding and Multilayer Bootstrap Network for Speaker Clustering

Zhang, X. (2016) · Interspeech (USB) · doi:10.21437/interspeech.2016-65 · Cited by 6

Improving Speaker Verification for Reverberant Conditions with Deep Neural Network Dereverberation Processing

Guzewich, P., & Zahorian, S. A. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-461 · Cited by 6

Optimal Mapping Loss: A Faster Loss for End-to-End Speaker Diarization

Lin, Q., Li, T., Yang, L., Wang, J., & Li, M. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-18 · Cited by 6

Orthogonal Training for Text-Independent Speaker Verification

Zhu, Y., & Mak, B. K.-W. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053198 · Cited by 6

Local variability vector for text-independent speaker verification

Chen, L., Lee, K. A., Ma, B., Guo, W., Li, H., & Dai, L. (2014) · International Symposium on Chinese Spoken Language Processing (ISCSLP) · doi:10.1109/iscslp.2014.6936577 · Cited by 5

Applying compensation techniques on i-vectors extracted from short-test utterances for speaker verification using deep neural network

Yang, I.-H., Heo, H.-S., Yoon, S.-H., & Yu, H.-J. (2017) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2017.7953206 · Cited by 5

X-VECTORS: ROBUST NEURAL EMBEDDINGS FOR SPEAKER RECOGNITION

Snyder, D. (2020) · Cited by 5

Orthogonality Regularizations for End-to-End Speaker Verification

Zhu, Y., & Mak, B. K.-W. (2020) · The Speaker and Language Recognition Workshop (Odyssey) · doi:10.21437/odyssey.2020-3 · Cited by 4

Semi-supervised Nuisance-attribute Networks for Domain Adaptation

Lin, W., Mak, M., Tu, Y., & Chien, J. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682752 · Cited by 4

Total Variability Layer in Deep Neural Network Embeddings for Speaker Verification

Travadi, R., & Narayanan, S. S. (2019) · IEEE Signal Processing Letters · doi:10.1109/lsp.2019.2910400 · Cited by 4

A Memory Augmented Architecture for Continuous Speaker Identification in Meetings

Flemotomos, N., & Dimitriadis, D. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053152 · Cited by 4

Speaker Embeddings Incorporating Acoustic Conditions for Diarization

Higuchi, Y., Suzuki, M., & Kurata, G. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054273 · Cited by 3

An Investigation of Speaker Clustering Algorithms in Adverse Acoustic Environments

Li, M.-Z., & Zhang, X.-L. (2018) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.23919/apsipa.2018.8659665 · Cited by 2

Speaker diarisation using 2D self-attentive combination of embeddingsPreprint

Sun, G., Zhang, C., & Woodland, P. C. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.03190 · Cited by 2

A Generalized Framework for Domain Adaptation of PLDA in Speaker RecognitionPreprint

Wang, Q., Okabe, K., Lee, K. A., & Koshinaka, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.08815 · Cited by 1

A review of deep learning techniques for speech processing

Mehrish, A., Majumder, N., Bharadwaj, R., Mihalcea, R., & Poria, S. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.101869 · Cited by 389

Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey

Wang, T., Zheng, P., Li, S., & Wang, L. (2023) · Advanced Intelligent Systems · doi:10.1002/aisy.202300359 · Cited by 231

CAM++: A Fast and Efficient Network for Speaker Verification Using Context-Aware Masking

Wang, H., Zheng, S., Chen, Y., Cheng, L., & Chen, Q. (2023) · INTERSPEECH 2023 · doi:10.21437/interspeech.2023-1513 · Cited by 150

Deep Spoken Keyword Spotting: An Overview

López‐Espejo, I., Tan, Z., Hansen, J. H. L., & Jensen, J. (2021) · IEEE Access · doi:10.1109/access.2021.3139508 · Cited by 157

A Survey of Speaker Recognition: Fundamental Theories, Recognition Methods and Opportunities

Kabir, M. M., Mridha, M. F., Shin, J., Jahan, I., & Ohi, A. Q. (2021) · IEEE Access · doi:10.1109/access.2021.3084299 · Cited by 135

Speaker Recognition: Progression and challenges

Al-Irahyim, Y. F., & Mahmood, Q. (2021) · Mağallaẗ al-tarbiyaẗ wa-al-ʻilm · doi:10.33899/edusj.2021.129802.1150

A review of speaker diarization: Recent advances with deep learning

Park, T., Kanda, N., Dimitriadis, D., Han, K. J., Watanabe, S., & Narayanan, S. S. (2021) · Computer Speech & Language · doi:10.1016/j.csl.2021.101317 · Cited by 405

Speaker Recognition through Deep Learning Techniques

Shome, N., Sarkar, A., Ghosh, A. K., Laskar, R. H., & Kashyap, R. (2023) · Periodica Polytechnica Electrical Engineering and Computer Science · doi:10.3311/ppee.20971 · Cited by 17

A deep learning approach for speaker recognition

Hourri, S., & Kharroubi, J. (2019) · International Journal of Speech Technology · doi:10.1007/s10772-019-09665-y · Cited by 44

An overview of speaker recognition

Liu, J., Chen, C. L. P., Li, T., Zuo, Y., & He, P. (2019) · Trends in Computer Science and Information Technology · doi:10.17352/tcsit.000009 · Cited by 3