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11/02/2022
Internal Language Model Estimation based Adaptive Language Model Fusion for Domain Adaptation
ASR model deployment environment is ever-changing, and the incoming spee...
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11/01/2022
Speech-text based multi-modal training with bidirectional attention for improved speech recognition
To let the state-of-the-art end-to-end ASR model enjoy data efficiency, ...
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10/28/2022
Improving short-video speech recognition using random utterance concatenation
One of the limitations in end-to-end automatic speech recognition framew...
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10/26/2022
Reducing Language confusion for Code-switching Speech Recognition with Token-level Language Diarization
Code-switching (CS) refers to the phenomenon that languages switch withi...
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07/09/2022
Intermediate-layer output Regularization for Attention-based Speech Recognition with Shared Decoder
Intermediate layer output (ILO) regularization by means of multitask tra...
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07/09/2022
Internal Language Model Estimation based Language Model Fusion for Cross-Domain Code-Switching Speech Recognition
Internal Language Model Estimation (ILME) based language model (LM) fusi...
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01/26/2022
Internal language model estimation through explicit context vector learning for attention-based encoder-decoder ASR
An end-to-end (E2E) speech recognition model implicitly learns a biased ...
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07/22/2021
Multitask-Based Joint Learning Approach To Robust ASR For Radio Communication Speech
To realize robust end-to-end Automatic Speech Recognition(E2E ASR) under...
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10/23/2020
Enriching Under-Represented Named-Entities To Improve Speech Recognition Performance
Automatic speech recognition (ASR) for under-represented named-entity (U...
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10/22/2020
The NTU-AISG Text-to-speech System for Blizzard Challenge 2020
We report our NTU-AISG Text-to-speech (TTS) entry systems for the Blizza...
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10/22/2020
A multilingual approach to joint Speech and Accent Recognition with DNN-HMM framework
Human can perform multi-task recognition from speech. For instance, huma...
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05/21/2020
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning
In this work, we study leveraging extra text data to improve low-resourc...
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05/18/2020
Approaches to Improving Recognition of Underrepresented Named Entities in Hybrid ASR Systems
In this paper, we present a series of complementary approaches to improv...
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01/05/2020
Spatial-Scale Aligned Network for Fine-Grained Recognition
Existing approaches for fine-grained visual recognition focus on learnin...
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11/25/2019
Independent language modeling architecture for end-to-end ASR
The attention-based end-to-end (E2E) automatic speech recognition (ASR) ...
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04/08/2019
Constrained Output Embeddings for End-to-End Code-Switching Speech Recognition with Only Monolingual Data
The lack of code-switch training data is one of the major concerns in th...
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04/08/2019
Enriching Rare Word Representations in Neural Language Models by Embedding Matrix Augmentation
The neural language models (NLM) achieve strong generalization capabilit...
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11/01/2018
On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition
Code-switching (CS) refers to a linguistic phenomenon where a speaker us...
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06/16/2018
Study of Semi-supervised Approaches to Improving English-Mandarin Code-Switching Speech Recognition
In this paper, we present our overall efforts to improve the performance...
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11/06/2017
