b'Zhong Meng'

research

∙ 09/15/2023

Augmenting conformers with structured state space models for online speech recognition

Online speech recognition, where the model only accesses context to the ...

0 Haozhe Shan, et al. ∙

research

∙ 08/11/2023

Improving Joint Speech-Text Representations Without Alignment

The last year has seen astonishing progress in text-prompted image gener...

0 Cal Peyser, et al. ∙

research

∙ 03/02/2023

Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

We introduce the Universal Speech Model (USM), a single large model that...

0 Yu Zhang, et al. ∙

research

∙ 02/16/2023

JEIT: Joint End-to-End Model and Internal Language Model Training for Speech Recognition

We propose JEIT, a joint end-to-end (E2E) model and internal language mo...

0 Zhong Meng, et al. ∙

research

∙ 10/31/2022

Modular Hybrid Autoregressive Transducer

Text-only adaptation of a transducer model remains challenging for end-t...

0 Zhong Meng, et al. ∙

research

∙ 03/30/2022

Streaming Speaker-Attributed ASR with Token-Level Speaker Embeddings

This paper presents a streaming speaker-attributed automatic speech reco...

0 Naoyuki Kanda, et al. ∙

research

∙ 02/02/2022

Streaming Multi-Talker ASR with Token-Level Serialized Output Training

This paper proposes a token-level serialized output training (t-SOT), a ...

0 Naoyuki Kanda, et al. ∙

research

∙ 10/28/2021

Continuous Speech Separation with Recurrent Selective Attention Network

While permutation invariant training (PIT) based continuous speech separ...

0 Yixuan Zhang, et al. ∙

research

∙ 10/27/2021

Separating Long-Form Speech with Group-Wise Permutation Invariant Training

Multi-talker conversational speech processing has drawn many interests f...

0 Wangyou Zhang, et al. ∙

research

∙ 10/07/2021

Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR

This paper presents Transcribe-to-Diarize, a new approach for neural spe...

0 Naoyuki Kanda, et al. ∙

research

∙ 10/06/2021

Internal Language Model Adaptation with Text-Only Data for End-to-End Speech Recognition

Text-only adaptation of an end-to-end (E2E) model remains a challenging ...

0 Zhong Meng, et al. ∙

research

∙ 09/27/2021

Factorized Neural Transducer for Efficient Language Model Adaptation

In recent years, end-to-end (E2E) based automatic speech recognition (AS...

0 Xie Chen, et al. ∙

research

∙ 07/06/2021

A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio

Speaker-attributed automatic speech recognition (SA-ASR) is a task to re...

0 Naoyuki Kanda, et al. ∙

research

∙ 06/04/2021

Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition

Integrating external language models (LMs) into end-to-end (E2E) models ...

0 Zhong Meng, et al. ∙

research

∙ 04/05/2021

End-to-End Speaker-Attributed ASR with Transformer

This paper presents our recent effort on end-to-end speaker-attributed a...

0 Naoyuki Kanda, et al. ∙

research

∙ 03/31/2021

Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone

Transcribing meetings containing overlapped speech with only a single di...

0 Naoyuki Kanda, et al. ∙

research

∙ 03/03/2021

Continuous Speech Separation with Ad Hoc Microphone Arrays

Speech separation has been shown effective for multi-talker speech recog...

0 Dongmei Wang, et al. ∙

research

∙ 02/02/2021

Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition

The efficacy of external language model (LM) integration with existing e...

0 Zhong Meng, et al. ∙

research

∙ 01/06/2021

Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings

An end-to-end (E2E) speaker-attributed automatic speech recognition (SA-...

0 Xuankai Chang, et al. ∙

research

∙ 11/05/2020

Exploring End-to-End Multi-channel ASR with Bias Information for Meeting Transcription

Joint optimization of multi-channel front-end and automatic speech recog...

0 Xiaofei Wang, et al. ∙

research

∙ 11/03/2020

Minimum Bayes Risk Training for End-to-End Speaker-Attributed ASR

Recently, an end-to-end speaker-attributed automatic speech recognition ...

0 Naoyuki Kanda, et al. ∙

research

∙ 11/03/2020

Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition

The external language models (LM) integration remains a challenging task...

0 Zhong Meng, et al. ∙

research

∙ 10/23/2020

On Minimum Word Error Rate Training of the Hybrid Autoregressive Transducer

Hybrid Autoregressive Transducer (HAT) is a recently proposed end-to-end...

0 Liang Lu, et al. ∙

research

∙ 08/11/2020

Investigation of End-To-End Speaker-Attributed ASR for Continuous Multi-Talker Recordings

Recently, an end-to-end (E2E) speaker-attributed automatic speech recogn...

0 Naoyuki Kanda, et al. ∙

research

∙ 07/30/2020

Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability

Because of its streaming nature, recurrent neural network transducer (RN...

0 Jinyu Li, et al. ∙

research

∙ 06/19/2020

Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of Any Number of Speakers

We propose an end-to-end speaker-attributed automatic speech recognition...

0 Naoyuki Kanda, et al. ∙

research

∙ 04/25/2020

Active Voice Authentication

Active authentication refers to a new mode of identity verification in w...

0 Zhong Meng, et al. ∙

research

∙ 04/25/2020

L-Vector: Neural Label Embedding for Domain Adaptation

We propose a novel neural label embedding (NLE) scheme for the domain ad...

0 Zhong Meng, et al. ∙

research

∙ 03/28/2020

Serialized Output Training for End-to-End Overlapped Speech Recognition

This paper proposes serialized output training (SOT), a novel framework ...

0 Naoyuki Kanda, et al. ∙

research

∙ 03/17/2020

High-Accuracy and Low-Latency Speech Recognition with Two-Head Contextual Layer Trajectory LSTM Model

While the community keeps promoting end-to-end models over conventional ...

0 Jinyu Li, et al. ∙

research

∙ 01/30/2020

Continuous speech separation: dataset and analysis

This paper describes a dataset and protocols for evaluating continuous s...

0 Zhuo Chen, et al. ∙

research

∙ 01/06/2020

Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition

Teacher-student (T/S) has shown to be effective for domain adaptation of...

2 Zhong Meng, et al. ∙

research

∙ 01/06/2020

Character-Aware Attention-Based End-to-End Speech Recognition

Predicting words and subword units (WSUs) as the output has shown to be ...

5 Zhong Meng, et al. ∙

research

∙ 11/09/2019

Speaker Adaptation for Attention-Based End-to-End Speech Recognition

We propose three regularization-based speaker adaptation approaches to a...

0 Zhong Meng, et al. ∙

research

∙ 04/29/2019

Adversarial Speaker Adaptation

We propose a novel adversarial speaker adaptation (ASA) scheme, in which...

0 Zhong Meng, et al. ∙

research

∙ 04/29/2019

Adversarial Speaker Verification

The use of deep networks to extract embeddings for speaker recognition h...

0 Zhong Meng, et al. ∙

research

∙ 04/28/2019

Attentive Adversarial Learning for Domain-Invariant Training

Adversarial domain-invariant training (ADIT) proves to be effective in s...

0 Zhong Meng, et al. ∙

research

∙ 04/28/2019

Conditional Teacher-Student Learning

The teacher-student (T/S) learning has been shown to be effective for a ...

0 Zhong Meng, et al. ∙

research

∙ 09/06/2018

Cycle-Consistent Speech Enhancement

Feature mapping using deep neural networks is an effective approach for ...

0 Zhong Meng, et al. ∙

research

∙ 09/06/2018

Adversarial Feature-Mapping for Speech Enhancement

Feature-mapping with deep neural networks is commonly used for single-ch...

0 Zhong Meng, et al. ∙

research

∙ 04/02/2018

Speaker-Invariant Training via Adversarial Learning

We propose a novel adversarial multi-task learning scheme, aiming at act...

0 Zhong Meng, et al. ∙

research

∙ 04/02/2018

Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation

The teacher-student (T/S) learning has been shown effective in unsupervi...

0 Zhong Meng, et al. ∙

research

∙ 11/21/2017

Deep Long Short-Term Memory Adaptive Beamforming Networks For Multichannel Robust Speech Recognition

Far-field speech recognition in noisy and reverberant conditions remains...

0 Zhong Meng, et al. ∙

research

∙ 11/21/2017

Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition

Unsupervised domain adaptation of speech signal aims at adapting a well-...

0 Zhong Meng, et al. ∙

Zhong Meng

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