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A Deep Speaker Embedding Transfer Method for Speaker Verification
2019Recently a kind of deep speaker embedding called x-vector has been proposed. It is extracted from deep neural network and considered as a strong contender for next-generation representation for speaker recognition. However, training such DNNs requires a lot of data, usually thousands of hours.
Kai Zhou +3 more
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Speaker Diarization using Embedding Vectors
2020 28th Signal Processing and Communications Applications Conference (SIU), 2020In recent years, with the rapid increase of voice data, solutions are being sought extensively for examination and indexing in the field of speech processing. One of these solutions is the speaker diarization, which is used to examine speech records that include multi-speaker.
Toruk, M Mesut +2 more
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Speaker-Aware Target Speaker Enhancement by Jointly Learning with Speaker Embedding Extraction
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020Deep learning based speech separation approaches have received great interest, among which the recent speaker-aware speech enhancement methods are promising for solving difficulties such as arbitrary source permutation and unknown number of sources. In this paper, we propose a novel training framework which jointly learns the speaker-conditioned target
Xuan Ji +6 more
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Self Attentive Context dependent Speaker Embedding for Speaker Verification
2020 National Conference on Communications (NCC), 2020In the recent past, Deep neural networks became the most successful approach to extract the speaker embeddings. Among the existing methods, the x-vector system, that extracts a fixed dimensional representation from varying length speech signal, became the most successful approach.
Sreekanth Sankala +2 more
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2020
Deep neural networks (DNN) have recently been widely used in speaker recognition systems, achieving state-of-the-art performance on various benchmarks. The x-vector architecture is especially popular in this research community, due to its excellent performance and manageable computational complexity.
Georges, Munir +2 more
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Deep neural networks (DNN) have recently been widely used in speaker recognition systems, achieving state-of-the-art performance on various benchmarks. The x-vector architecture is especially popular in this research community, due to its excellent performance and manageable computational complexity.
Georges, Munir +2 more
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Disentangled Speaker Embedding for Robust Speaker Verification
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Lu Yi 0001, Man-Wai Mak
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Speaker-Corrupted Embeddings for Online Speaker Diarization
Interspeech 2019, 2019Omid Ghahabi, Volker Fischer 0002
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Language Agnostic Speaker Embedding for Cross-Lingual Personalized Speech Generation
IEEE/ACM Transactions on Audio Speech and Language Processing, 2021Xiaohai Tian, Haizhou Li, Yi Zhou
exaly
ANSD-MA-MSE: Adaptive Neural Speaker Diarization Using Memory-Aware Multi-Speaker Embedding
IEEE/ACM Transactions on Audio Speech and Language Processing, 2023Chin-Hui Lee, Jun Du, Maokui He
exaly
Selective Deep Speaker Embedding Enhancement for Speaker Verification
The Speaker and Language Recognition Workshop (Odyssey 2020), 2020Jee-Weon Jung +4 more
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