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 211–220 of 332 papers

Title	Date	Tasks	Status
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder	Jul 31, 2018	Generative Adversarial NetworkSpeech Synthesis	—Unverified
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks	Oct 30, 2018	Image GenerationSpeech Synthesis	—Unverified
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis	Apr 4, 2024	Language ModelingLanguage Modelling	—Unverified
Real-time Incremental Speech-to-Speech Translation of Dialogs	Jun 1, 2012	Machine TranslationSpeech Recognition	—Unverified
ReCAB-VAE: Gumbel-Softmax Variational Inference Based on Analytic Divergence	May 9, 2022	Speech Synthesistext-to-speech	—Unverified
Refer-iTTS: A System for Referring in Spoken Installments to Objects in Real-World Images	Sep 1, 2017	Referring ExpressionReferring expression generation	—Unverified
Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability	Apr 3, 2021	Emotion Recognitionreinforcement-learning	—Unverified
DLPO: Diffusion Model Loss-Guided Reinforcement Learning for Fine-Tuning Text-to-Speech Diffusion Models	May 23, 2024	Image Generationreinforcement-learning	—Unverified
ReVISE: Self-Supervised Speech Resynthesis with Visual Input for Universal and Generalized Speech Enhancement	Dec 21, 2022	Audio-Visual Speech RecognitionResynthesis	—Unverified
ReVISE: Self-Supervised Speech Resynthesis With Visual Input for Universal and Generalized Speech Regeneration	Jan 1, 2023	Audio-Visual Speech RecognitionResynthesis	—Unverified

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All datasets LJSpeech 20000 utterances CMUDict 0.7b HUI speech corpus Thorsten voice 21.02 neutral Trinity Speech-Gesture Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	NaturalSpeech	Audio Quality MOS	4.56	—	Unverified
2	VITS	Audio Quality MOS	4.43	—	Unverified
3	Grad-TTS + HiFiGAN (1000 steps)	Audio Quality MOS	4.37	—	Unverified
4	FastSpeech 2 + HiFiGAN	Audio Quality MOS	4.34	—	Unverified
5	Glow-TTS + HiFiGAN	Audio Quality MOS	4.34	—	Unverified
6	FastSpeech 2 + HiFiGAN	Audio Quality MOS	4.32	—	Unverified
7	FastDiff (4 steps)	Audio Quality MOS	4.28	—	Unverified
8	FastDiff-TTS	Audio Quality MOS	4.03	—	Unverified
9	Transformer TTS (Mel + WaveGlow)	Audio Quality MOS	3.88	—	Unverified
10	FastSpeech (Mel + WaveGlow)	Audio Quality MOS	3.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mia	10-keyword Speech Commands dataset	16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Token-Level Ensemble Distillation	Phoneme Error Rate	4.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Tacotron 2	Mean Opinion Score	3.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Tacotron 2	Mean Opinion Score	3.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Match-TTSG	MOS	3.7	—	Unverified