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 211–220 of 332 papers

Title	Date	Tasks	Status	Hype
Semi-supervised URL Segmentation with Recurrent Neural NetworksPre-trained on Knowledge Graph Entities	Nov 5, 2020	Chinese Word SegmentationSpeech Synthesis	CodeCode Available	1
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework	Nov 4, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Incremental Machine Speech Chain Towards Enabling Listening while Speaking in Real-time	Nov 4, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Effective Deep Learning Models for Automatic Diacritization of Arabic Text	Nov 1, 2020	Arabic Text DiacritizationDecoder	CodeCode Available	1
GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis	Oct 23, 2020	Graph AttentionGraph Neural Network	—Unverified	0
An Investigation of the Relation Between Grapheme Embeddings and Pronunciation for Tacotron-based Systems	Oct 21, 2020	Grapheme-to-Phoneme ConversionRelation	—Unverified	0
End-to-End Text-to-Speech using Latent Duration based on VQ-VAE	Oct 19, 2020	Speech Synthesistext-to-speech	—Unverified	0
MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response	Oct 8, 2020	Deep LearningPrognosis	CodeCode Available	0
Automatic Arabic Dialect Identification Systems for Written Texts: A Survey	Sep 26, 2020	Dialect IdentificationMachine Translation	—Unverified	0
Hierarchical Multi-Grained Generative Model for Expressive Speech Synthesis	Sep 17, 2020	Expressive Speech SynthesisSpeech Synthesis	—Unverified	0

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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