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 171–180 of 332 papers

Title	Date	Tasks	Status
Text-to-speech synthesis based on latent variable conversion using diffusion probabilistic model and variational autoencoder	Dec 16, 2022	Representation LearningSpeech Synthesis	—Unverified
Investigation of Japanese PnG BERT language model in text-to-speech synthesis for pitch accent language	Dec 16, 2022	Language ModelingLanguage Modelling	—Unverified
Grad-StyleSpeech: Any-speaker Adaptive Text-to-Speech Synthesis with Diffusion Models	Nov 17, 2022	Speech Synthesistext-to-speech	—Unverified
Technology Pipeline for Large Scale Cross-Lingual Dubbing of Lecture Videos into Multiple Indian Languages	Nov 1, 2022	ChunkingRhythm	—Unverified
Virtuoso: Massive Multilingual Speech-Text Joint Semi-Supervised Learning for Text-To-Speech	Oct 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era	Oct 6, 2022	Speech Synthesistext-to-speech	—Unverified
Controllable Accented Text-to-Speech Synthesis	Sep 22, 2022	Speech Synthesistext-to-speech	—Unverified
EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models	Sep 22, 2022	Speech Synthesistext-to-speech	—Unverified
Mlphon: A Multifunctional Grapheme-Phoneme Conversion Tool Using Finite State Transducers	Sep 5, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available
BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language model	Jul 4, 2022	Language ModelingLanguage Modelling	—Unverified

Show:10 25 50

← PrevPage 18 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