Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency

Understand

We propose a dynamic encoder transducer (DET) for on-device speech recognition.

• One DET model scales to multiple devices with different computation capacities without retraining or finetuning.
• To trading off accuracy and latency, DET assigns different encoders to decode different parts of an utterance.
• We apply and compare the layer dropout and the collaborative learning for DET training.