List of papers which have been read.
- Pre-trained Text Representations for Improving Front-End Text Processing in Mandarin Text-to-Speech Synthesis (Interspeech 2019)
- A unified sequence-to-sequence front-end model for Mandarin text-to-speech synthesis (ICASSP 2020)
- A hybrid text normalization system using multi-head self-attention for mandarin (ICASSP 2020)
- Tacotron V1: Tacotron: Towards End-to-End Speech Synthesis (Interspeech 2017)
- Tacotron V2: Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions (ICASSP 2018)
- Deep Voice V1: Deep Voice: Real-time Neural Text-to-Speech (ICML 2017)
- Deep Voice V2: Deep Voice 2: Multi-Speaker Neural Text-to-Speech (NeurIPS 2017)
- Deep Voice V3: Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning (ICLR 2018)
- Transformer-TTS: Neural Speech Synthesis with Transformer Network (AAAI 2019)
- Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis (ICASSP 2020)
- DurIAN: DurIAN: Duration Informed Attention Network For Multimodal Synthesis (2019)
- Flowtron (flow based): Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis (2020)
- ParaNet: Non-Autoregressive Neural Text-to-Speech (ICML 2020)
- FastSpeech: FastSpeech: Fast, Robust and Controllable Text to Speech (NeurIPS 2019)
- JDI-T: JDI-T: Jointly trained Duration Informed Transformer for Text-To-Speech without Explicit Alignment (2020)
- EATS: End-to-End Adversarial Text-to-Speech (2020)
- FastSpeech 2: FastSpeech 2: Fast and High-Quality End-to-End Text to Speech (2020)
- FastPitch: FastPitch: Parallel Text-to-speech with Pitch Prediction (2020)
- Glow-TTS (flow based, Monotonic Attention): Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search (2020)
- Flow-TTS (flow based): Flow-TTS: A Non-Autoregressive Network for Text to Speech Based on Flow (ICASSP 2020)
- SpeedySpeech: SpeedySpeech: Efficient Neural Speech Synthesis (Interspeech 2020)
- Monotonic Attention: Online and Linear-Time Attention by Enforcing Monotonic Alignments (ICML 2017)
- Monotonic Chunkwise Attention: Monotonic Chunkwise Attention (ICLR 2018)
- Forward Attention in Sequence-to-sequence Acoustic Modelling for Speech Synthesis (ICASSP 2018)
- RNN-T for TTS: Initial investigation of an encoder-decoder end-to-end TTS framework using marginalization of monotonic hard latent alignments (2019)
- Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis (ICASSP 2020)
- Semi-Supervised Training for Improving Data Efficiency in End-to-End Speech Synthesis (2018)
- Almost Unsupervised Text to Speech and Automatic Speech Recognition (ICML 2019)
- Unsupervised Learning For Sequence-to-sequence Text-to-speech For Low-resource Languages (Interspeech 2020)
- WaveNet: WaveNet: A Generative Model for Raw Audio (2016)
- WaveRNN: Efficient Neural Audio Synthesis (ICML 2018)
- LPCNet: LPCNet: Improving Neural Speech Synthesis Through Linear Prediction (ICASSP 2019)
- GAN-TTS: High Fidelity Speech Synthesis with Adversarial Networks (2019)
- WaveGAN: Adversarial Audio Synthesis (2018)
- MultiBand-WaveRNN: DurIAN: Duration Informed Attention Network For Multimodal Synthesis (2019)
- Parallel-WaveNet: Parallel WaveNet: Fast High-Fidelity Speech Synthesis (2017)
- WaveGlow: WaveGlow: A Flow-based Generative Network for Speech Synthesis (2018)
- Parallel-WaveGAN: Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram (2019)
- MelGAN: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis (NeurIPS 2019)
- MultiBand-MelGAN: Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech (2020)
- VocGAN: VocGAN: A High-Fidelity Real-time Vocoder with a Hierarchically-nested Adversarial Network (Interspeech 2020)
- ReferenceEncoder-Tacotron: Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron (ICML 2018)
- GST-Tacotron: Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis (ICML 2018)
- GMVAE-Tacotron2: Hierarchical Generative Modeling for Controllable Speech Synthesis (ICLR 2019)
- Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis (2018)
- (Multi-style Decouple): Multi-reference Tacotron by Intercross Training for Style Disentangling,Transfer and Control in Speech Synthesis (InterSpeech 2019)
- Mellotron: Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens (2019)
- Flowtron (flow based): Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis (2020)
- Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis (ICASSP 2020)
- Controllable Neural Prosody Synthesis (Interspeech 2020)
- Sample Efficient Adaptive Text-to-Speech (ICLR 2019)
- SV-Tacotron: Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (NeurIPS 2018)
- Deep Voice V3: Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning (ICLR 2018)
- Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddings (ICASSP 2020)
- MultiSpeech: MultiSpeech: Multi-Speaker Text to Speech with Transformer (2020)
- SC-WaveRNN: Speaker Conditional WaveRNN: Towards Universal Neural Vocoder for Unseen Speaker and Recording Conditions (Interspeech 2020)
- (introduce PPG into voice conversion): Phonetic posteriorgrams for many-to-one voice conversion without parallel data training (2016)
- A Vocoder-free WaveNet Voice Conversion with Non-Parallel Data (2019)
- TTS-Skins: TTS Skins: Speaker Conversion via ASR (2019)
- AutoVC: AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss (2019)
- CycleGAN-VC V1: Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks (2017)
- CycleGAN-VC V2: CycleGAN-VC2: Improved CycleGAN-based Non-parallel Voice Conversion (2019)
- StarGAN-VC: StarGAN-VC: non-parallel many-to-many Voice Conversion Using Star Generative Adversarial Networks (2018)
- VAE-VC (VAE based): Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder (2016)
- Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion (2019)
- One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization (2019)
- Cotatron (combine text information with voice conversion system): Cotatron: Transcription-Guided Speech Encoder for Any-to-Many Voice Conversion without Parallel Data (2020)
- XiaoIce Band: XiaoIce Band: A Melody and Arrangement Generation Framework for Pop Music (KDD 2018)
- PitchNet: PitchNet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network (ICASSP 2020)
- Mellotron: Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens (2019)
- ByteSing: ByteSing: A Chinese Singing Voice Synthesis System Using Duration Allocated Encoder-Decoder Acoustic Models and WaveRNN Vocoders (2020)
- JukeBox: Jukebox: A Generative Model for Music (2020)
- XiaoIce Sing: XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System (2020)
- DurIAN-SC: DurIAN-SC: Duration Informed Attention Network based Singing Voice Conversion System (Interspeech 2020)
- Speech-to-Singing Conversion based on Boundary Equilibrium GAN (Interspeech 2020)
- Audio-Word2Vec: Audio Word2Vec: Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Autoencoder (2016)
- SpeechBERT: SpeechBERT: An Audio-and-text Jointly Learned Language Model for End-to-end Spoken Question Answering (2019)
- Improving Transformer-based Speech Recognition Using Unsupervised Pre-training (2019)
- TasNet: TasNet: time-domain audio separation network for real-time, single-channel speech separation (ICASSP 2018)
- A Study of Non-autoregressive Model for Sequence Generation (ACL 2020)
- Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement (EMNLP 2018)
- Non-Autoregressive Neural Machine Translation (ICLR 2018)
- Non-Autoregressive Machine Translation with Auxiliary Regularization (AAAI 2019)
- Mask-Predict: Parallel Decoding of Conditional Masked Language Models (EMNLP 2019)