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Text-To-Speech Synthesis

Text-To-Speech Synthesis is a machine learning task that involves converting written text into spoken words. The goal is to generate synthetic speech that sounds natural and resembles human speech as closely as possible.

Papers

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Showing 151–175 of 332 papers

TitleStatusHype
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech SynthesisCode2
The PartialSpoof Database and Countermeasures for the Detection of Short Fake Speech Segments Embedded in an Utterance—0
SOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis—0
VQTTS: High-Fidelity Text-to-Speech Synthesis with Self-Supervised VQ Acoustic Feature—0
Unsupervised Text-to-Speech Synthesis by Unsupervised Automatic Speech RecognitionCode1
Applying Syntaxx2013Prosody Mapping Hypothesis and Prosodic Well-Formedness Constraints to Neural Sequence-to-Sequence Speech Synthesis—0
AutoTTS: End-to-End Text-to-Speech Synthesis through Differentiable Duration Modeling—0
ECAPA-TDNN for Multi-speaker Text-to-speech SynthesisCode0
Text-free non-parallel many-to-many voice conversion using normalising flows—0
iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier TransformCode2
Generative Modeling for Low Dimensional Speech Attributes with Neural Spline FlowsCode2
Deep Performer: Score-to-Audio Music Performance Synthesis—0
Multi-Stage Deep Transfer Learning for EmIoT-enabled Human-Computer Interaction—0
Transformer-based Models of Text Normalization for Speech Applications—0
Multi-speaker Multi-style Text-to-speech Synthesis With Single-speaker Single-style Training Data Scenarios—0
Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale CorpusCode1
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyoneCode1
Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance—0
Systematic Inequalities in Language Technology Performance across the World's LanguagesCode0
Fine-grained style control in Transformer-based Text-to-speech SynthesisCode1
Towards Lifelong Learning of Multilingual Text-To-Speech SynthesisCode0
Environment Aware Text-to-Speech Synthesis—0
EdiTTS: Score-based Editing for Controllable Text-to-SpeechCode1
Prosody-TTS: An end-to-end speech synthesis system with prosody control—0
Neural Speech Synthesis in German—0
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All datasetsLJSpeech20000 utterancesCMUDict 0.7bHUI speech corpusThorsten voice 21.02 neutralTrinity Speech-Gesture Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NaturalSpeechAudio Quality MOS4.56—Unverified
2VITSAudio Quality MOS4.43—Unverified
3Grad-TTS + HiFiGAN (1000 steps)Audio Quality MOS4.37—Unverified
4FastSpeech 2 + HiFiGANAudio Quality MOS4.34—Unverified
5Glow-TTS + HiFiGANAudio Quality MOS4.34—Unverified
6FastSpeech 2 + HiFiGANAudio Quality MOS4.32—Unverified
7FastDiff (4 steps)Audio Quality MOS4.28—Unverified
8FastDiff-TTSAudio Quality MOS4.03—Unverified
9Transformer TTS (Mel + WaveGlow)Audio Quality MOS3.88—Unverified
10FastSpeech (Mel + WaveGlow)Audio Quality MOS3.84—Unverified
#ModelMetricClaimedVerifiedStatus
1Mia10-keyword Speech Commands dataset16—Unverified
#ModelMetricClaimedVerifiedStatus
1Token-Level Ensemble DistillationPhoneme Error Rate4.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.74—Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Match-TTSGMOS3.7—Unverified