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08/14/2023
O-1: Self-training with Oracle and 1-best Hypothesis
We introduce O-1, a new self-training objective to reduce training bias ...
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06/13/2023
Large-scale Language Model Rescoring on Long-form Data
In this work, we study the impact of Large-scale Language Models (LLM) o...
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03/10/2023
Robust Knowledge Distillation from RNN-T Models With Noisy Training Labels Using Full-Sum Loss
This work studies knowledge distillation (KD) and addresses its constrai...
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10/31/2022
Modular Hybrid Autoregressive Transducer
Text-only adaptation of a transducer model remains challenging for end-t...
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09/13/2022
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition
Attention layers are an integral part of modern end-to-end automatic spe...
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10/08/2020
Leveraging Unpaired Text Data for Training End-to-End Speech-to-Intent Systems
Training an end-to-end (E2E) neural network speech-to-intent (S2I) syste...
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09/30/2020
End-to-End Spoken Language Understanding Without Full Transcripts
An essential component of spoken language understanding (SLU) is slot fi...
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06/16/2020
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Current methods for learning visually grounded language from videos ofte...
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01/20/2020
Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard-300
It is generally believed that direct sequence-to-sequence (seq2seq) spee...
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08/09/2019
Challenging the Boundaries of Speech Recognition: The MALACH Corpus
There has been huge progress in speech recognition over the last several...
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04/17/2019
Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation
Conventional automatic speech recognition (ASR) systems trained from fra...
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03/29/2019
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition
Direct acoustics-to-word (A2W) systems for end-to-end automatic speech r...
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02/07/2018
Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition
The performance of automatic speech recognition systems degrades with in...
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12/08/2017
Building competitive direct acoustics-to-word models for English conversational speech recognition
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have re...
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03/22/2017
Direct Acoustics-to-Word Models for English Conversational Speech Recognition
Recent work on end-to-end automatic speech recognition (ASR) has shown t...
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03/06/2017
English Conversational Telephone Speech Recognition by Humans and Machines
One of the most difficult speech recognition tasks is accurate recogniti...
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01/13/2017
End-to-End ASR-free Keyword Search from Speech
End-to-end (E2E) systems have achieved competitive results compared to c...
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11/27/2016
Invariant Representations for Noisy Speech Recognition
Modern automatic speech recognition (ASR) systems need to be robust unde...
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12/22/2014
Diverse Embedding Neural Network Language Models
We propose Diverse Embedding Neural Network (DENN), a novel architecture...
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12/28/2013