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09/05/2023
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models
Automatic Speech Recognition (ASR) models need to be optimized for speci...
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07/21/2023
Prompting Large Language Models with Speech Recognition Abilities
Large language models have proven themselves highly flexible, able to so...
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05/30/2023
Towards Selection of Text-to-speech Data to Augment ASR Training
This paper presents a method for selecting appropriate synthetic speech ...
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05/21/2023
Multi-Head State Space Model for Speech Recognition
State space models (SSMs) have recently shown promising results on small...
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02/17/2023
Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free and Hybrid Approaches
Wake word detection exists in most intelligent homes and portable device...
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07/25/2022
Learning a Dual-Mode Speech Recognition Model via Self-Pruning
There is growing interest in unifying the streaming and full-context aut...
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03/30/2022
Federated Domain Adaptation for ASR with Full Self-Supervision
Cross-device federated learning (FL) protects user privacy by collaborat...
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10/15/2021
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet
From wearables to powerful smart devices, modern automatic speech recogn...
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10/07/2021
Streaming Transformer Transducer Based Speech Recognition Using Non-Causal Convolution
This paper improves the streaming transformer transducer for speech reco...
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07/09/2021
Noisy Training Improves E2E ASR for the Edge
Automatic speech recognition (ASR) has become increasingly ubiquitous on...
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04/06/2021
Flexi-Transducer: Optimizing Latency, Accuracy and Compute forMulti-Domain On-Device Scenarios
Often, the storage and computational constraints of embeddeddevices dema...
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04/06/2021
Dissecting User-Perceived Latency of On-Device E2E Speech Recognition
As speech-enabled devices such as smartphones and smart speakers become ...
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04/05/2021
Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion
How to leverage dynamic contextual information in end-to-end speech reco...
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02/23/2021
Memory-efficient Speech Recognition on Smart Devices
Recurrent transducer models have emerged as a promising solution for spe...
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11/11/2020
Efficient Knowledge Distillation for RNN-Transducer Models
Knowledge Distillation is an effective method of transferring knowledge ...
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11/05/2020
Alignment Restricted Streaming Recurrent Neural Network Transducer
There is a growing interest in the speech community in developing Recurr...
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10/26/2020
Improved Neural Language Model Fusion for Streaming Recurrent Neural Network Transducer
Recurrent Neural Network Transducer (RNN-T), like most end-to-end speech...
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06/02/2020
Analyzing the Quality and Stability of a Streaming End-to-End On-Device Speech Recognizer
The demand for fast and accurate incremental speech recognition increase...
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03/28/2020
A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency
Thus far, end-to-end (E2E) models have not been shown to outperform stat...
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09/26/2019
Optimizing Speech Recognition For The Edge
While most deployed speech recognition systems today still run on server...
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11/15/2018
