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09/19/2023
End-to-End Speech Recognition Contextualization with Large Language Models
In recent years, Large Language Models (LLMs) have garnered significant ...
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07/22/2023
Modality Confidence Aware Training for Robust End-to-End Spoken Language Understanding
End-to-end (E2E) spoken language understanding (SLU) systems that genera...
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11/10/2022
Massively Multilingual ASR on 70 Languages: Tokenization, Architecture, and Generalization Capabilities
End-to-end multilingual ASR has become more appealing because of several...
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04/04/2022
Deliberation Model for On-Device Spoken Language Understanding
We propose a novel deliberation-based approach to end-to-end (E2E) spoke...
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03/29/2022
Streaming parallel transducer beam search with fast-slow cascaded encoders
Streaming ASR with strict latency constraints is required in many speech...
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01/28/2022
Neural-FST Class Language Model for End-to-End Speech Recognition
We propose Neural-FST Class Language Model (NFCLM) for end-to-end speech...
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10/11/2021
Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric
Measuring automatic speech recognition (ASR) system quality is critical ...
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06/16/2021
Collaborative Training of Acoustic Encoders for Speech Recognition
On-device speech recognition requires training models of different sizes...
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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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04/05/2021
Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency
We propose a dynamic encoder transducer (DET) for on-device speech recog...
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04/05/2021
Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding
Word Error Rate (WER) has been the predominant metric used to evaluate t...
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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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11/16/2020
Deep Shallow Fusion for RNN-T Personalization
End-to-end models in general, and Recurrent Neural Network Transducer (R...
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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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11/03/2020
Streaming Attention-Based Models with Augmented Memory for End-to-End Speech Recognition
Attention-based models have been gaining popularity recently for their s...
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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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05/18/2020
Weak-Attention Suppression For Transformer Based Speech Recognition
Transformers, originally proposed for natural language processing (NLP) ...
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11/27/2019
AIPNet: Generative Adversarial Pre-training of Accent-invariant Networks for End-to-end Speech Recognition
As one of the major sources in speech variability, accents have posed a ...
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11/05/2019
RNN-T For Latency Controlled ASR With Improved Beam Search
Neural transducer-based systems such as RNN Transducers (RNN-T) for auto...
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10/28/2019
Transformer-Transducer: End-to-End Speech Recognition with Self-Attention
We explore options to use Transformer networks in neural transducer for ...
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10/22/2019
G2G: TTS-Driven Pronunciation Learning for Graphemic Hybrid ASR
Grapheme-based acoustic modeling has recently been shown to outperform p...
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10/22/2019
Transformer-based Acoustic Modeling for Hybrid Speech Recognition
We propose and evaluate transformer-based acoustic models (AMs) for hybr...
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10/02/2019
From Senones to Chenones: Tied Context-Dependent Graphemes for Hybrid Speech Recognition
There is an implicit assumption that traditional hybrid approaches for a...
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12/05/2018
End-to-end contextual speech recognition using class language models and a token passing decoder
End-to-end modeling (E2E) of automatic speech recognition (ASR) blends a...
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11/06/2017
Improved training for online end-to-end speech recognition systems
Achieving high accuracy with end-to-end speech recognizers requires care...
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11/06/2017
Towards Language-Universal End-to-End Speech Recognition
Building speech recognizers in multiple languages typically involves rep...
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08/17/2017
Large-Scale Domain Adaptation via Teacher-Student Learning
High accuracy speech recognition requires a large amount of transcribed ...
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01/16/2013
