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Deep Neural Network Embeddings for Text-Independent Speaker Verification
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Citations
Cited by
VoxCeleb2: Deep Speaker Recognition
Chung, J. S., Nagrani, A., & Zisserman, A. (2018) · Interspeech 2018 · doi:10.21437/interspeech.2018-1929 · Cited by 2,256
Speaker Recognition from Raw Waveform with SincNet
Ravanelli, M., & Bengio, Y. (2018) · 2018 IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt.2018.8639585 · Cited by 896
Attentive Statistics Pooling for Deep Speaker Embedding
Okabe, K., Koshinaka, T., & Shinoda, K. (2018) · Interspeech 2018 · doi:10.21437/interspeech.2018-993 · Cited by 514
“Probabilistic linear discriminant analysis (PLDA) [13, 14] can also be used for measuring the distance between two utterance-level features [9, 10].”
BackgroundMethodInfluentialA 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
Speaker recognition based on deep learning: An overview
Bai, Z., & Zhang, X.-L. (2021) · Neural Networks · doi:10.1016/j.neunet.2021.03.004 · Cited by 386
Metadata
- Authors
- Snyder, D., Garcia-Romero, D., Povey, D., & Khudanpur, S.
- Venue
- Interspeech 2017
- Publisher
- ISCA
- Published
- 2017-08-20
- Pages
- 999-1003
- ISSN
- 2308-457X (ISSN-L)
- OpenAlex
- W2748488820
- Cited by
- 739
- References
- 0
- FWCI
- 39.25
- Type
- conference paper
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
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- CoChat. (2026). Citation check: Deep Neural Network Embeddings for Text-Independent Speaker Verification. https://app.cochat.ai/papers/10.21437/interspeech.2017-620
- The paper
- Snyder, D., Garcia-Romero, D., Povey, D., & Khudanpur, S. (2017). Deep Neural Network Embeddings for Text-Independent Speaker Verification. Interspeech 2017. https://doi.org/10.21437/interspeech.2017-620
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
