62 citations · 655 across the 97 of their papers we have counts for
31 papers · 1 filter
Phonetic Posteriorgrams based Many-to-Many Singing Voice Conversion via Adversarial Training
Haohan Guo, Heng Lu, Na Hu +5
This paper describes an end-to-end adversarial singing voice conversion (EA-SVC) approach. It can directly generate arbitrary singing waveform by given phonetic posteriorgram (PPG)…
Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition
Binbin Zhang, Di Wu, Zhuoyuan Yao +7
In this paper, we present a novel two-pass approach to unify streaming and non-streaming end-to-end (E2E) speech recognition in a single model. Our model adopts the hybrid CTC/atte…
TFGAN: Time and Frequency Domain Based Generative Adversarial Network for High-fidelity Speech Synthesis
Qiao Tian, Yi Chen, Zewang Zhang +4
Recently, GAN based speech synthesis methods, such as MelGAN, have become very popular. Compared to conventional autoregressive based methods, parallel structures based generators…
Context-aware RNNLM Rescoring for Conversational Speech Recognition
Kun Wei, Pengcheng Guo, Hang Lv +2
Conversational speech recognition is regarded as a challenging task due to its free-style speaking and long-term contextual dependencies. Prior work has explored the modeling of lo…
Multi-Channel Automatic Speech Recognition Using Deep Complex Unet
Yuxiang Kong, Jian Wu, Quandong Wang +4
The front-end module in multi-channel automatic speech recognition (ASR) systems mainly use microphone array techniques to produce enhanced signals in noisy conditions with reverbe…
Controllable Emotion Transfer For End-to-End Speech Synthesis
Tao Li, Shan Yang, Liumeng Xue +1
Emotion embedding space learned from references is a straightforward approach for emotion transfer in encoder-decoder structured emotional text to speech (TTS) systems. However, th…
Adversarial Training for Multi-domain Speaker Recognition
Qing Wang, Wei Rao, Pengcheng Guo +1
In real-life applications, the performance of speaker recognition systems always degrades when there is a mismatch between training and evaluation data. Many domain adaptation meth…
Accent and Speaker Disentanglement in Many-to-many Voice Conversion
Zhichao Wang, Wenshuo Ge, Xiong Wang +6
This paper proposes an interesting voice and accent joint conversion approach, which can convert an arbitrary source speaker's voice to a target speaker with non-native accent. Thi…
Optimizing voice conversion network with cycle consistency loss of speaker identity
Hongqiang Du, Xiaohai Tian, Lei Xie +1
We propose a novel training scheme to optimize voice conversion network with a speaker identity loss function. The training scheme not only minimizes frame-level spectral loss, but…
Fine-grained Emotion Strength Transfer, Control and Prediction for Emotional Speech Synthesis
Yi Lei, Shan Yang, Lei Xie
This paper proposes a unified model to conduct emotion transfer, control and prediction for sequence-to-sequence based fine-grained emotional speech synthesis. Conventional emotion…
Cascade RNN-Transducer: Syllable Based Streaming On-device Mandarin Speech Recognition with a Syllable-to-Character Converter
Xiong Wang, Zhuoyuan Yao, Xian Shi +1
End-to-end models are favored in automatic speech recognition (ASR) because of its simplified system structure and superior performance. Among these models, recurrent neural networ…
Learn2Sing: Target Speaker Singing Voice Synthesis by learning from a Singing Teacher
Heyang Xue, Shan Yang, Yi Lei +2
Singing voice synthesis has been paid rising attention with the rapid development of speech synthesis area. In general, a studio-level singing corpus is usually necessary to produc…
The SLT 2021 children speech recognition challenge: Open datasets, rules and baselines
Fan Yu, Zhuoyuan Yao, Xiong Wang +6
Automatic speech recognition (ASR) has been significantly advanced with the use of deep learning and big data. However improving robustness, including achieving equally good perfor…
IEEE SLT 2021 Alpha-mini Speech Challenge: Open Datasets, Tracks, Rules and Baselines
Yihui Fu, Zhuoyuan Yao, Weipeng He +9
The IEEE Spoken Language Technology Workshop (SLT) 2021 Alpha-mini Speech Challenge (ASC) is intended to improve research on keyword spotting (KWS) and sound source location (SSL)…
DESNet: A Multi-channel Network for Simultaneous Speech Dereverberation, Enhancement and Separation
Yihui Fu, Jian Wu, Yanxin Hu +2
In this paper, we propose a multi-channel network for simultaneous speech dereverberation, enhancement and separation (DESNet). To enable gradient propagation and joint optimizatio…
AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification
Jingsong Wang, Tom Ko, Zhen Xu +4
The AutoSpeech challenge calls for automated machine learning (AutoML) solutions to automate the process of applying machine learning to speech processing tasks. These tasks, which…
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…
An End-to-end Architecture of Online Multi-channel Speech Separation
Jian Wu, Zhuo Chen, Jinyu Li +5
Multi-speaker speech recognition has been one of the keychallenges in conversation transcription as it breaks the singleactive speaker assumption employed by most state-of-the-arts…
Channel-wise Subband Input for Better Voice and Accompaniment Separation on High Resolution Music
Haohe Liu, Lei Xie, Jian Wu +1
This paper presents a new input format, channel-wise subband input (CWS), for convolutional neural networks (CNN) based music source separation (MSS) models in the frequency domain…
Data Efficient Voice Cloning from Noisy Samples with Domain Adversarial Training
Jian Cong, Shan Yang, Lei Xie +2
Data efficient voice cloning aims at synthesizing target speaker's voice with only a few enrollment samples at hand. To this end, speaker adaptation and speaker encoding are two ty…
NPU Speaker Verification System for INTERSPEECH 2020 Far-Field Speaker Verification Challenge
Li Zhang, Jian Wu, Lei Xie
This paper describes the NPU system submitted to Interspeech 2020 Far-Field Speaker Verification Challenge (FFSVC). We particularly focus on far-field text-dependent SV from single…
Exploiting Deep Sentential Context for Expressive End-to-End Speech Synthesis
Fengyu Yang, Shan Yang, Qinghua Wu +2
Attention-based seq2seq text-to-speech systems, especially those use self-attention networks (SAN), have achieved state-of-art performance. But an expressive corpus with rich proso…
The ASRU 2019 Mandarin-English Code-Switching Speech Recognition Challenge: Open Datasets, Tracks, Methods and Results
Xian Shi, Qiangze Feng, Lei Xie
Code-switching (CS) is a common phenomenon and recognizing CS speech is challenging. But CS speech data is scarce and there' s no common testbed in relevant research. This paper de…
Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals
Jing Shi, Xuankai Chang, Pengcheng Guo +5
Neural sequence-to-sequence models are well established for applications which can be cast as mapping a single input sequence into a single output sequence. In this work, we focus…