Speech Synthesis

Speech synthesis is the task of generating speech from some other modality like text, lip movements etc.

Please note that the leaderboards here are not really comparable between studies - as they use mean opinion score as a metric and collect different samples from Amazon Mechnical Turk.

( Image credit: WaveNet: A generative model for raw audio )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 951–960 of 1249 papers

Title	Date	Tasks	Status	Hype
Multi-Speaker End-to-End Speech Synthesis	Jul 9, 2019	Speech Synthesis	—Unverified	0
\'Evaluation objective de plongements pour la synth\`ese de parole guid\'ee par r\'eseaux de neurones (Objective evaluation of embeddings for speech synthesis guided by neural networks)	Jul 1, 2019	Speech Synthesis	—Unverified	0
Deep Residual Neural Networks for Audio Spoofing Detection	Jun 30, 2019	Speaker VerificationSpeech Synthesis	CodeCode Available	0
End-to-End Emotional Speech Synthesis Using Style Tokens and Semi-Supervised Training	Jun 26, 2019	Emotional Speech SynthesisEmotion Recognition	—Unverified	0
RUSLAN: Russian Spoken Language Corpus for Speech Synthesis	Jun 26, 2019	Speech Synthesistext-to-speech	—Unverified	0
A Unified Speaker Adaptation Method for Speech Synthesis using Transcribed and Untranscribed Speech with Backpropagation	Jun 18, 2019	DecoderSpeech Synthesis	—Unverified	0
Towards Transfer Learning for End-to-End Speech Synthesis from Deep Pre-Trained Language Models	Jun 17, 2019	DecoderSpeech Synthesis	—Unverified	0
Using generative modelling to produce varied intonation for speech synthesis	Jun 10, 2019	SentenceSpeech Synthesis	CodeCode Available	0
Effective Use of Variational Embedding Capacity in Expressive End-to-End Speech Synthesis	Jun 8, 2019	Expressive Speech SynthesisSpeech Synthesis	CodeCode Available	1
MelNet: A Generative Model for Audio in the Frequency Domain	Jun 4, 2019	Audio GenerationMusic Generation	CodeCode Available	0

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All datasets LibriTTS North American English LJSpeech Mandarin Chinese Blizzard Challenge 2013

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PeriodWave-Turbo-L	PESQ	4.45	—	Unverified
2	BigVGAN-v2	PESQ	4.36	—	Unverified
3	EVA-GAN-big	PESQ	4.35	—	Unverified
4	PeriodWave + FreeU	PESQ	4.25	—	Unverified
5	RFWave	PESQ	4.23	—	Unverified
6	BigVSAN (w/ snakebeta)	PESQ	4.12	—	Unverified
7	BigVSAN	PESQ	4.12	—	Unverified
8	EVA-GAN-base	PESQ	4.03	—	Unverified
9	BigVGAN	PESQ	4.03	—	Unverified
10	Vocos	PESQ	3.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Tacotron 2	Mean Opinion Score	4.53	—	Unverified
2	WaveNet (Linguistic)	Mean Opinion Score	4.34	—	Unverified
3	WaveNet (L+F)	Mean Opinion Score	4.21	—	Unverified
4	Tacotron	Mean Opinion Score	4	—	Unverified
5	HMM-driven concatenative	Mean Opinion Score	3.86	—	Unverified
6	LSTM-RNN parametric	Mean Opinion Score	3.67	—	Unverified
7	means	Mean Opinion Score	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BDDM vocoder	Mean Opinion Score	4.48	—	Unverified
2	DiffWave LARGE	Mean Opinion Score	4.44	—	Unverified
3	Neural HMM	Mean Opinion Score	3.24	—	Unverified
4	Neural HMM Ablation with 1 state per phone	Mean Opinion Score	2.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	WaveNet (L+F)	Mean Opinion Score	4.08	—	Unverified
2	LSTM-RNN parametric	Mean Opinion Score	3.79	—	Unverified
3	HMM-driven concatenative	Mean Opinion Score	3.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SampleRNN (2-tier)	NLL	1.39	—	Unverified
2	SampleRNN (3-tier)	NLL	1.39	—	Unverified