216 citations · 500 across the 47 of their papers we have counts for
11 papers · 1 filter
Consistent Training and Decoding For End-to-end Speech Recognition Using Lattice-free MMI
Jinchuan Tian, Jianwei Yu, Chao Weng +4
Recently, End-to-End (E2E) frameworks have achieved remarkable results on various Automatic Speech Recognition (ASR) tasks. However, Lattice-Free Maximum Mutual Information (LF-MMI…
Detect what you want: Target Sound Detection
Dongchao Yang, Helin Wang, Yuexian Zou +2
Human beings can perceive a target sound type from a multi-source mixture signal by the selective auditory attention, however, such functionality was hardly ever explored in machin…
Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorization
Brian Yan, Chunlei Zhang, Meng Yu +6
Conversational bilingual speech encompasses three types of utterances: two purely monolingual types and one intra-sententially code-switched type. In this work, we propose a genera…
Simple Attention Module based Speaker Verification with Iterative noisy label detection
Xiaoyi Qin, Na Li, Chao Weng +2
Recently, the attention mechanism such as squeeze-and-excitation module (SE) and convolutional block attention module (CBAM) has achieved great success in deep learning-based speak…
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio
Guoguo Chen, Shuzhou Chai, Guanbo Wang +18
This paper introduces GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training, and…
Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
Max W. Y. Lam, Jun Wang, Chao Weng +2
End-to-end speech recognition generally uses hand-engineered acoustic features as input and excludes the feature extraction module from its joint optimization. To extract learnable…
Enhancing Speaking Styles in Conversational Text-to-Speech Synthesis with Graph-based Multi-modal Context Modeling
Jingbei Li, Yi Meng, Chenyi Li +4
Comparing with traditional text-to-speech (TTS) systems, conversational TTS systems are required to synthesize speeches with proper speaking style confirming to the conversational…
Towards Robust Speaker Verification with Target Speaker Enhancement
Chunlei Zhang, Meng Yu, Chao Weng +1
This paper proposes the target speaker enhancement based speaker verification network (TASE-SVNet), an all neural model that couples target speaker enhancement and speaker embeddin…
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation
Helin Wang, Bo Wu, Lianwu Chen +7
In this paper, we exploit the effective way to leverage contextual information to improve the speech dereverberation performance in real-world reverberant environments. We propose…
VARA-TTS: Non-Autoregressive Text-to-Speech Synthesis based on Very Deep VAE with Residual Attention
Peng Liu, Yuewen Cao, Songxiang Liu +4
This paper proposes VARA-TTS, a non-autoregressive (non-AR) text-to-speech (TTS) model using a very deep Variational Autoencoder (VDVAE) with Residual Attention mechanism, which re…
Deep Learning based Multi-Source Localization with Source Splitting and its Effectiveness in Multi-Talker Speech Recognition
Aswin Shanmugam Subramanian, Chao Weng, Shinji Watanabe +2
Multi-source localization is an important and challenging technique for multi-talker conversation analysis. This paper proposes a novel supervised learning method using deep neural…