mlsanityData to 7 Oct 2026

Attention-Based Models for Text-Dependent Speaker Verification

arXiv 1710.10470 ↗First posted 28 Oct 2017eess.AS cs.LG cs.SDcited by 17

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Abstract (arXiv)

Attention-based models have recently shown great performance on a range of tasks, such as speech recognition, machine translation, and image captioning due to their ability to summarize relevant information that expands through the entire length of an input sequence. In this paper, we analyze the usage of attention mechanisms to the problem of sequence summarization in our end-to-end text-dependent speaker recognition system. We explore different topologies and their variants of the attention layer, and compare different pooling methods on the attention weights. Ultimately, we show that attention-based models can improves the Equal Error Rate (EER) of our speaker verification system by relatively 14% compared to our non-attention LSTM baseline model.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Oct 2017.

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Citing papers per year: 2021: 10; 2022: 5; 2023: 1; 2024: 1.

17 papers.

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  1. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  2. 2021Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Losscited by 25
  3. 2022Attentive Temporal Pooling for Conformer-based Streaming Language Identification in Long-form Speechcited by 6
  4. 2021Graph-based Label Propagation for Semi-Supervised Speaker Identificationcited by 4
  5. 2021Multi-user VoiceFilter-Lite via Attentive Speaker Embeddingcited by 4
  6. 2024Speech Rhythm-Based Speaker Embeddings Extraction from Phonemes and Phoneme Duration for Multi-Speaker Speech Synthesiscited by 3
  7. 2021Content-Aware Speaker Embeddings for Speaker Diarisationcited by 2
  8. 2021The NPU System for the 2020 Personalized Voice Trigger Challengecited by 2
  9. 2021Auto-KWS 2021 Challenge: Task, Datasets, and Baselinescited by 2
  10. 2021Phoneme-aware and Channel-wise Attentive Learning for Text DependentSpeaker Verificationcited by 2
  11. 2022Parameter-Free Attentive Scoring for Speaker Verificationcited by 2
  12. 2022Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challengecited by 2
5 more
  1. 2022Learning from human perception to improve automatic speaker verification in style-mismatched conditionscited by 2
  2. 2022Automatic Evaluation of Speaker Similaritycited by 2
  3. 2021Language ID Prediction from Speech Using Self-Attentive Pooling and 1D-Convolutionscited by 1
  4. 2021Low-Resource Spoken Language Identification Using Self-Attentive Pooling and Deep 1D Time-Channel Separable Convolutionscited by 0
  5. 2023Analyzing And Improving Neural Speaker Embeddings for ASRcited by 0