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05/12/2023
Accelerator-Aware Training for Transducer-Based Speech Recognition
Machine learning model weights and activations are represented in full-p...
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05/09/2023
Robust Acoustic and Semantic Contextual Biasing in Neural Transducers for Speech Recognition
Attention-based contextual biasing approaches have shown significant imp...
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04/03/2023
Dual-Attention Neural Transducers for Efficient Wake Word Spotting in Speech Recognition
We present dual-attention neural biasing, an architecture designed to bo...
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10/17/2022
Sub-8-bit quantization for on-device speech recognition: a regularization-free approach
For on-device automatic speech recognition (ASR), quantization aware tra...
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09/29/2022
ConvRNN-T: Convolutional Augmented Recurrent Neural Network Transducers for Streaming Speech Recognition
The recurrent neural network transducer (RNN-T) is a prominent streaming...
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07/05/2022
Compute Cost Amortized Transformer for Streaming ASR
We present a streaming, Transformer-based end-to-end automatic speech re...
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06/30/2022
Sub-8-Bit Quantization Aware Training for 8-Bit Neural Network Accelerator with On-Device Speech Recognition
We present a novel sub-8-bit quantization-aware training (S8BQAT) scheme...
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05/26/2022
Contextual Adapters for Personalized Speech Recognition in Neural Transducers
Personal rare word recognition in end-to-end Automatic Speech Recognitio...
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05/11/2022
A neural prosody encoder for end-ro-end dialogue act classification
Dialogue act classification (DAC) is a critical task for spoken language...
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11/05/2021
Context-Aware Transformer Transducer for Speech Recognition
End-to-end (E2E) automatic speech recognition (ASR) systems often have d...
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10/31/2021
FANS: Fusing ASR and NLU for on-device SLU
Spoken language understanding (SLU) systems translate voice input comman...
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08/30/2021
Multi-Channel Transformer Transducer for Speech Recognition
Multi-channel inputs offer several advantages over single-channel, to im...
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06/16/2021
End-to-End Spoken Language Understanding for Generalized Voice Assistants
End-to-end (E2E) spoken language understanding (SLU) systems predict utt...
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06/14/2021
CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition
We propose a simple yet effective method to compress an RNN-Transducer (...
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06/11/2021
Exploiting Large-scale Teacher-Student Training for On-device Acoustic Models
We present results from Alexa speech teams on semi-supervised learning (...
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02/09/2021
Sparsification via Compressed Sensing for Automatic Speech Recognition
In order to achieve high accuracy for machine learning (ML) applications...
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02/08/2021
End-to-End Multi-Channel Transformer for Speech Recognition
Transformers are powerful neural architectures that allow integrating di...
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11/18/2020
Tie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding
End-to-end (E2E) spoken language understanding (SLU) systems can infer t...
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08/12/2020
End-to-End Neural Transformer Based Spoken Language Understanding
Spoken language understanding (SLU) refers to the process of inferring t...
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08/06/2020
Semantic Complexity in End-to-End Spoken Language Understanding
End-to-end spoken language understanding (SLU) models are a class of mod...
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07/08/2020
Streaming End-to-End Bilingual ASR Systems with Joint Language Identification
Multilingual ASR technology simplifies model training and deployment, bu...
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09/26/2018