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Transformer in action: a comparative study of transformer-based acoustic models for large scale speech recognition applications.

, , , , , , and . CoRR, (2020)

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Multi-basis adaptive neural network for rapid adaptation in speech recognition., and . ICASSP, page 4315-4319. IEEE, (2015)A machine learning method for the large-scale evaluation of urban visual environment., , and . CoRR, (2016)Incentive-compatible adaptive-width channel allocation for non-cooperative wireless networks., , , , and . Int. J. Sens. Networks, 18 (3/4): 227-237 (2015)Improved Repetitive Control with Enhanced Active Damping Method for 400Hz Inverter., , , , and . IECON, page 1-6. IEEE, (2023)Deep Activation Mixture Model for Speech Recognition., and . INTERSPEECH, page 1611-1615. ISCA, (2017)Flexi-Transducer: Optimizing Latency, Accuracy and Compute for Multi-Domain On-Device Scenarios., , , , , , , , , and . Interspeech, page 2107-2111. ISCA, (2021)Structured deep neural networks for speech recognition.. University of Cambridge, UK, (2018)British Library, EThOS.I-Vectors and Structured Neural Networks for Rapid Adaptation of Acoustic Models., , , and . IEEE ACM Trans. Audio Speech Lang. Process., 25 (4): 818-828 (2017)Stimulated training for automatic speech recognition and keyword search in limited resource conditions., , , , and . ICASSP, page 4830-4834. IEEE, (2017)Combining i-vector representation and structured neural networks for rapid adaptation., , and . ICASSP, page 5000-5004. IEEE, (2016)