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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 271–280 of 332 papers

Title	Date	Tasks	Status
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks	Oct 30, 2018	Image GenerationSpeech Synthesis	—Unverified
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention	Oct 29, 2018	Speech Synthesistext-to-speech	—Unverified
Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent language	Oct 29, 2018	Speech Synthesistext-to-speech	CodeCode Available
A Challenge Set and Methods for Noun-Verb Ambiguity	Oct 1, 2018	Speech Synthesistext-to-speech	—Unverified
Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis	Aug 4, 2018	Speech Synthesistext-to-speech	—Unverified
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
The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems	Jun 25, 2018	Speech Emotion RecognitionSpeech Synthesis	CodeCode Available
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis	Jun 12, 2018	Speaker VerificationSpeech Synthesis	CodeCode Available
Design and Development of Speech Corpora for Air Traffic Control Training	May 1, 2018	Automatic Speech Recognition (ASR)Speech Recognition	—Unverified
Improving homograph disambiguation with supervised machine learning	May 1, 2018	BIG-bench Machine LearningSpeech Synthesis	—Unverified

Show:10 25 50

← PrevPage 28 of 34Next →

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