SOTAVerified

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

Showing 226–250 of 1249 papers

TitleStatusHype
VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers—0
Autoregressive Diffusion Transformer for Text-to-Speech Synthesis—0
Spectral Codecs: Improving Non-Autoregressive Speech Synthesis with Spectrogram-Based Audio Codecs—0
Small-E: Small Language Model with Linear Attention for Efficient Speech SynthesisCode2
Improving Audio Codec-based Zero-Shot Text-to-Speech Synthesis with Multi-Modal Context and Large Language Model—0
Style Mixture of Experts for Expressive Text-To-Speech Synthesis—0
StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task LearningCode5
Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis—0
ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style ControlCode3
Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training—0
Enhancing Zero-shot Text-to-Speech Synthesis with Human Feedback—0
Very Low Complexity Speech Synthesis Using Framewise Autoregressive GAN (FARGAN) with Pitch PredictionCode5
Multilingual Prosody Transfer: Comparing Supervised & Transfer Learning—0
DLPO: Diffusion Model Loss-Guided Reinforcement Learning for Fine-Tuning Text-to-Speech Diffusion Models—0
Evaluating Text-to-Speech Synthesis from a Large Discrete Token-based Speech Language Model—0
Expressivity and Speech Synthesis—0
UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal PromptsCode1
FlashSpeech: Efficient Zero-Shot Speech SynthesisCode3
Retrieval-Augmented Audio Deepfake Detection—0
Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications—0
Llama-VITS: Enhancing TTS Synthesis with Semantic AwarenessCode2
HyperTTS: Parameter Efficient Adaptation in Text to Speech using HypernetworksCode1
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis—0
Leveraging the Interplay Between Syntactic and Acoustic Cues for Optimizing Korean TTS Pause Formation—0
PSCodec: A Series of High-Fidelity Low-bitrate Neural Speech Codecs Leveraging Prompt Encoders—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PeriodWave-Turbo-LPESQ4.45—Unverified
2BigVGAN-v2PESQ4.36—Unverified
3EVA-GAN-bigPESQ4.35—Unverified
4PeriodWave + FreeUPESQ4.25—Unverified
5RFWavePESQ4.23—Unverified
6BigVSAN (w/ snakebeta)PESQ4.12—Unverified
7BigVSANPESQ4.12—Unverified
8EVA-GAN-basePESQ4.03—Unverified
9BigVGANPESQ4.03—Unverified
10VocosPESQ3.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score4.53—Unverified
2WaveNet (Linguistic)Mean Opinion Score4.34—Unverified
3WaveNet (L+F)Mean Opinion Score4.21—Unverified
4TacotronMean Opinion Score4—Unverified
5HMM-driven concatenativeMean Opinion Score3.86—Unverified
6LSTM-RNN parametricMean Opinion Score3.67—Unverified
7meansMean Opinion Score0—Unverified
#ModelMetricClaimedVerifiedStatus
1BDDM vocoderMean Opinion Score4.48—Unverified
2DiffWave LARGEMean Opinion Score4.44—Unverified
3Neural HMMMean Opinion Score3.24—Unverified
4Neural HMM Ablation with 1 state per phoneMean Opinion Score2.68—Unverified
#ModelMetricClaimedVerifiedStatus
1WaveNet (L+F)Mean Opinion Score4.08—Unverified
2LSTM-RNN parametricMean Opinion Score3.79—Unverified
3HMM-driven concatenativeMean Opinion Score3.47—Unverified
#ModelMetricClaimedVerifiedStatus
1SampleRNN (2-tier)NLL1.39—Unverified
2SampleRNN (3-tier)NLL1.39—Unverified