mlsanityData to 7 Oct 2026

Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entities

arXiv 1912.09251 ↗First posted 14 Dec 2019eess.AS cs.LG cs.SDcited by 41

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Abstract (arXiv)

We study the effectiveness of several techniques to personalize end-to-end speech models and improve the recognition of proper names relevant to the user. These techniques differ in the amounts of user effort required to provide supervision, and are evaluated on how they impact speech recognition performance. We propose using keyword-dependent precision and recall metrics to measure vocabulary acquisition performance. We evaluate the algorithms on a dataset that we designed to contain names of persons that are difficult to recognize. Therefore, the baseline recall rate for proper names in this dataset is very low: 2.4%. A data synthesis approach we developed brings it to 48.6%, with no need for speech input from the user. With speech input, if the user corrects only the names, the name recall rate improves to 64.4%. If the user corrects all the recognition errors, we achieve the best recall of 73.5%. To eliminate the need to upload user data and store personalized models on a server, we focus on performing the entire personalization workflow on a mobile device.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Dec 2019.

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Citing papers per year: 2021: 8; 2022: 8; 2023: 12; 2024: 12; 2025: 1.

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  1. 2021Recent Advances in End-to-End Automatic Speech Recognitioncited by 138
  2. 2022FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objectscited by 91
  3. 2022TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulationcited by 47
  4. 2021Factorized Neural Transducer for Efficient Language Model Adaptationcited by 31
  5. 2021Personalization Strategies for End-to-End Speech Recognition Systemscited by 26
  6. 2021Fast Contextual Adaptation with Neural Associative Memory for On-Device Personalized Speech Recognitioncited by 25
  7. 2023DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classificationcited by 23
  8. 2021Efficient Federated Meta-Learning over Multi-Access Wireless Networkscited by 13
  9. 2022Fast and accurate factorized neural transducer for text adaption of end-to-end speech recognition modelscited by 11
  10. 2023CB-Conformer: Contextual biasing Conformer for biased word recognitioncited by 11
  11. 2021The History of Speech Recognition to the Year 2030cited by 10
  12. 2023APLA: Additional Perturbation for Latent Noise with Adversarial Training Enables Consistencycited by 9
29 more
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  2. 2022A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Datacited by 7
  3. 2022UserLibri: A Dataset for ASR Personalization Using Only Textcited by 6
  4. 2021On-Device Personalization of Automatic Speech Recognition Models for Disordered Speechcited by 5
  5. 2023Retraining-free Customized ASR for Enharmonic Words Based on a Named-Entity-Aware Model and Phoneme Similarity Estimationcited by 5
  6. 2021Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environmentscited by 4
  7. 2023Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunitiescited by 4
  8. 2023SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappingscited by 4
  9. 2024CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimatorscited by 4
  10. 2024FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learningcited by 4
  11. 2024Locality enhanced dynamic biasing and sampling strategies for contextual ASRcited by 3
  12. 2022BERT WEAVER: Using WEight AVERaging to enable lifelong learning for transformer-based models in biomedical semantic search enginescited by 2
  13. 2023Improved Factorized Neural Transducer Model For text-only Domain Adaptationcited by 2
  14. 2023The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections through Federated Learningcited by 2
  15. 2024Learning Correspondence for Deformable Objectscited by 2
  16. 2024Safe Deep Model-Based Reinforcement Learning with Lyapunov Functionscited by 2
  17. 2024Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptationcited by 2
  18. 2024CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertaintycited by 2
  19. 2022A Knowledge Distillation-Based Backdoor Attack in Federated Learningcited by 1
  20. 2023Emphasizing Unseen Words: New Vocabulary Acquisition for End-to-End Speech Recognitioncited by 1
  21. 2023Hybrid Attention-based Encoder-decoder Model for Efficient Language Model Adaptationcited by 1
  22. 2023MobileASR: A resource-aware on-device learning framework for user voice personalization applications on mobile phonescited by 0
  23. 2023Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customizationcited by 0
  24. 2024Towards Improving Learning from Demonstration Algorithms via MCMC Methodscited by 0
  25. 2024Theoretical Analysis for Expectation-Maximization-Based Multi-Model 3D Registrationcited by 0
  26. 2024Rocket Landing Control with Grid Fins and Path-following using MPCcited by 0
  27. 2024Federated Learning of Large ASR Models in the Real Worldcited by 0
  28. 2024Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognitioncited by 0
  29. 2025Accelerating MoE Model Inference with Expert Shardingcited by 0