Jinyu Li

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Microsoft

Principal Science Lead at Microsoft

Streaming Multi-talker Speech Recognition with Joint Speaker Identification

In multi-talker scenarios such as meetings and conversations, speech pro...
04/05/2021 ∙ by Liang Lu, et al. ∙ 0 ∙ share

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

The efficacy of external language model (LM) integration with existing e...
02/02/2021 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Streaming end-to-end multi-talker speech recognition

End-to-end multi-talker speech recognition is an emerging research trend...
11/26/2020 ∙ by Liang Lu, et al. ∙ 0 ∙ share

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Listen, Look and Deliberate: Visual context-aware speech recognition using pre-trained text-video representations

In this study, we try to address the problem of leveraging visual signal...
11/08/2020 ∙ by Shahram Ghorbani, et al. ∙ 0 ∙ share

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Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis

Multi-speaker speech recognition of unsegmented recordings has diverse a...
11/03/2020 ∙ by Desh Raj, et al. ∙ 0 ∙ share

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

The external language models (LM) integration remains a challenging task...
11/03/2020 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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On Minimum Word Error Rate Training of the Hybrid Autoregressive Transducer

Hybrid Autoregressive Transducer (HAT) is a recently proposed end-to-end...
10/23/2020 ∙ by Liang Lu, et al. ∙ 0 ∙ share

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Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer

With its strong modeling capacity that comes from a multi-head and multi...
10/23/2020 ∙ by Sanyuan Chen, et al. ∙ 0 ∙ share

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Microsoft Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2020

This paper describes the Microsoft speaker diarization system for monaur...
10/22/2020 ∙ by Xiong Xiao, et al. ∙ 0 ∙ share

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Developing Real-time Streaming Transformer Transducer for Speech Recognition on Large-scale Dataset

Recently, Transformer based end-to-end models have achieved great succes...
10/22/2020 ∙ by Xie Chen, et al. ∙ 0 ∙ share

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Speaker Separation Using Speaker Inventories and Estimated Speech

We propose speaker separation using speaker inventories and estimated sp...
10/20/2020 ∙ by Peidong Wang, et al. ∙ 0 ∙ share

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An End-to-end Architecture of Online Multi-channel Speech Separation

Multi-speaker speech recognition has been one of the keychallenges in co...
09/07/2020 ∙ by Jian Wu, et al. ∙ 0 ∙ share

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Adaptation Algorithms for Speech Recognition: An Overview

We present a structured overview of adaptation algorithms for neural net...
08/14/2020 ∙ by Peter Bell, et al. ∙ 0 ∙ share

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Continuous Speech Separation with Conformer

Continuous speech separation plays a vital role in complicated speech re...
08/13/2020 ∙ by Sanyuan Chen, et al. ∙ 0 ∙ share

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Transfer Learning Approaches for Streaming End-to-End Speech Recognition System

Transfer learning (TL) is widely used in conventional hybrid automatic s...
08/12/2020 ∙ by Vikas Joshi, et al. ∙ 0 ∙ share

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

Because of its streaming nature, recurrent neural network transducer (RN...
07/30/2020 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition

Recently, there has been a strong push to transition from hybrid models ...
05/28/2020 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Exploring Transformers for Large-Scale Speech Recognition

While recurrent neural networks still largely define state-of-the-art sp...
05/19/2020 ∙ by Liang Lu, et al. ∙ 0 ∙ share

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Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition

Recently, the recurrent neural network transducer (RNN-T) architecture h...
05/01/2020 ∙ by Hu Hu, et al. ∙ 0 ∙ share

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L-Vector: Neural Label Embedding for Domain Adaptation

We propose a novel neural label embedding (NLE) scheme for the domain ad...
04/25/2020 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Minimum Latency Training Strategies for Streaming Sequence-to-Sequence ASR

Recently, a few novel streaming attention-based sequence-to-sequence (S2...
04/10/2020 ∙ by Hirofumi Inaguma, et al. ∙ 0 ∙ share

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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 ...
03/17/2020 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Continuous speech separation: dataset and analysis

This paper describes a dataset and protocols for evaluating continuous s...
01/30/2020 ∙ by Zhuo Chen, et al. ∙ 0 ∙ share

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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...
01/06/2020 ∙ by Zhong Meng, et al. ∙ 2 ∙ share

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

Predicting words and subword units (WSUs) as the output has shown to be ...
01/06/2020 ∙ by Zhong Meng, et al. ∙ 5 ∙ share

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Semantic Mask for Transformer based End-to-End Speech Recognition

Attention-based encoder-decoder model has achieved impressive results fo...
12/06/2019 ∙ by Chengyi Wang, et al. ∙ 0 ∙ share

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

We propose three regularization-based speaker adaptation approaches to a...
11/09/2019 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Improving RNN Transducer Modeling for End-to-End Speech Recognition

In the last few years, an emerging trend in automatic speech recognition...
09/26/2019 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Adversarial Speaker Adaptation

We propose a novel adversarial speaker adaptation (ASA) scheme, in which...
04/29/2019 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Adversarial Speaker Verification

The use of deep networks to extract embeddings for speaker recognition h...
04/29/2019 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Attentive Adversarial Learning for Domain-Invariant Training

Adversarial domain-invariant training (ADIT) proves to be effective in s...
04/28/2019 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Conditional Teacher-Student Learning

The teacher-student (T/S) learning has been shown to be effective for a ...
04/28/2019 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Speaker Adaptation for End-to-End CTC Models

We propose two approaches for speaker adaptation in end-to-end (E2E) aut...
01/04/2019 ∙ by Ke Li, et al. ∙ 0 ∙ share

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Advancing Acoustic-to-Word CTC Model with Attention and Mixed-Units

The acoustic-to-word model based on the Connectionist Temporal Classific...
12/31/2018 ∙ by Amit Das, et al. ∙ 0 ∙ share

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Cycle-Consistent Speech Enhancement

Feature mapping using deep neural networks is an effective approach for ...
09/06/2018 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Adversarial Feature-Mapping for Speech Enhancement

Feature-mapping with deep neural networks is commonly used for single-ch...
09/06/2018 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Layer Trajectory LSTM

It is popular to stack LSTM layers to get better modeling power, especia...
08/28/2018 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Recent Progresses in Deep Learning based Acoustic Models (Updated)

In this paper, we summarize recent progresses made in deep learning base...
04/25/2018 ∙ by Dong Yu, et al. ∙ 0 ∙ share

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Developing Far-Field Speaker System Via Teacher-Student Learning

In this study, we develop the keyword spotting (KWS) and acoustic model ...
04/14/2018 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Speaker-Invariant Training via Adversarial Learning

We propose a novel adversarial multi-task learning scheme, aiming at act...
04/02/2018 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation

The teacher-student (T/S) learning has been shown effective in unsupervi...
04/02/2018 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Cracking the cocktail party problem by multi-beam deep attractor network

While recent progresses in neural network approaches to single-channel s...
03/29/2018 ∙ by Zhuo Chen, et al. ∙ 0 ∙ share

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Advancing Acoustic-to-Word CTC Model

The acoustic-to-word model based on the connectionist temporal classific...
03/15/2018 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Advancing Connectionist Temporal Classification With Attention Modeling

In this study, we propose advancing all-neural speech recognition by dir...
03/15/2018 ∙ by Amit Das, et al. ∙ 0 ∙ share

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Acoustic-To-Word Model Without OOV

Recently, the acoustic-to-word model based on the Connectionist Temporal...
11/28/2017 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition

Unsupervised domain adaptation of speech signal aims at adapting a well-...
11/21/2017 ∙ by Zhong Meng, et al. ∙ 0 ∙ share

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Improved training for online end-to-end speech recognition systems

Achieving high accuracy with end-to-end speech recognizers requires care...
11/06/2017 ∙ by Suyoun Kim, et al. ∙ 0 ∙ share

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Large-Scale Domain Adaptation via Teacher-Student Learning

High accuracy speech recognition requires a large amount of transcribed ...
08/17/2017 ∙ by Jinyu Li, et al. ∙ 0 ∙ share

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Progressive Joint Modeling in Unsupervised Single-channel Overlapped Speech Recognition

Unsupervised single-channel overlapped speech recognition is one of the ...
07/21/2017 ∙ by Zhehuai Chen, et al. ∙ 0 ∙ share

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End-to-End Attention based Text-Dependent Speaker Verification

A new type of End-to-End system for text-dependent speaker verification ...
01/03/2017 ∙ by Shi-Xiong Zhang, et al. ∙ 0 ∙ share

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Jinyu Li

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