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 71–80 of 332 papers

Title	Date	Tasks	Status	Hype	Score
Effective Deep Learning Models for Automatic Diacritization of Arabic Text	Nov 1, 2020	Arabic Text DiacritizationDecoder	CodeCode Available	1	5
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning	Nov 7, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
EdiTTS: Score-based Editing for Controllable Text-to-Speech	Oct 6, 2021	Speech SynthesisSpeech-to-Text	CodeCode Available	1	5
Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder	Nov 7, 2022	Speech Synthesistext-to-speech	CodeCode Available	1	5
Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities	Dec 1, 2020	Chinese Word SegmentationSpeech Synthesis	CodeCode Available	1	5
Unsupervised Text-to-Speech Synthesis by Unsupervised Automatic Speech Recognition	Mar 29, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior	Jun 11, 2021	Audio GenerationDenoising	CodeCode Available	0	5
Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish	May 31, 2022	Machine TranslationSpeech Synthesis	CodeCode Available	0	5
Non-Autoregressive Neural Text-to-Speech	May 21, 2019	text-to-speechText to Speech	CodeCode Available	0	5
Phrase break prediction with bidirectional encoder representations in Japanese text-to-speech synthesis	Apr 26, 2021	Language ModelingLanguage Modelling	CodeCode Available	0	5

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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