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 261–270 of 332 papers

Title	Date	Tasks	Status	Hype
Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis	Mar 27, 2019	Emotional Speech SynthesisExpressive Speech Synthesis	CodeCode Available	1
Generative adversarial network-based glottal waveform model for statistical parametric speech synthesis	Mar 14, 2019	Generative Adversarial NetworkSpeech Synthesis	—Unverified	0
Exploring Transfer Learning for Low Resource Emotional TTS	Jan 14, 2019	Deep LearningEmotional Speech Synthesis	CodeCode Available	1
AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms	Nov 9, 2018	GPUImage Captioning	—Unverified	0
End-to-End Feedback Loss in Speech Chain Framework via Straight-Through Estimator	Oct 31, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks	Oct 30, 2018	Image GenerationSpeech Synthesis	—Unverified	0
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention	Oct 29, 2018	Speech Synthesistext-to-speech	—Unverified	0
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	0
A Challenge Set and Methods for Noun-Verb Ambiguity	Oct 1, 2018	Speech Synthesistext-to-speech	—Unverified	0
Neural Speech Synthesis with Transformer Network	Sep 19, 2018	DecoderMachine Translation	CodeCode Available	2

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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