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

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Showing 1101–1150 of 1249 papers

TitleStatusHype
Semi-supervised learning for continuous emotional intensity controllable speech synthesis with disentangled representations—0
Continuous Expressive Speaking Styles Synthesis based on CVSM and MR-HMM—0
Continuous Speech Synthesis using per-token Latent Diffusion—0
Continuous Wavelet Vocoder-based Decomposition of Parametric Speech Waveform Synthesis—0
Controllable Accented Text-to-Speech Synthesis—0
Controllable Context-aware Conversational Speech Synthesis—0
Controllable Data Generation by Deep Learning: A Review—0
Controllable Generation of Artificial Speaker Embeddings through Discovery of Principal Directions—0
Controllable Neural Prosody Synthesis—0
Controllable neural text-to-speech synthesis using intuitive prosodic features—0
Controllable Sequence-To-Sequence Neural TTS with LPCNET Backend for Real-time Speech Synthesis on CPU—0
Controllable speech synthesis by learning discrete phoneme-level prosodic representations—0
Controllable Prosody Generation With Partial Inputs—0
Corpus Generation for Voice Command in Smart Home and the Effect of Speech Synthesis on End-to-End SLU—0
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models—0
Visual-speech Synthesis of Exaggerated Corrective Feedback—0
Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models—0
CPJD Corpus: Crowdsourced Parallel Speech Corpus of Japanese Dialects—0
Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform—0
Creating New Voices using Normalizing Flows—0
Creating Personalized Synthetic Voices from Post-Glossectomy Speech with Guided Diffusion Models—0
Cross-lingual Knowledge Distillation via Flow-based Voice Conversion for Robust Polyglot Text-To-Speech—0
Cross-lingual Low Resource Speaker Adaptation Using Phonological Features—0
Cross-lingual Multi-speaker Text-to-speech Synthesis for Voice Cloning without Using Parallel Corpus for Unseen Speakers—0
Cross-lingual Multispeaker Text-to-Speech under Limited-Data Scenario—0
Cross-lingual Prosody Transfer for Expressive Machine Dubbing—0
Cross-Lingual Text-to-Speech Using Multi-Task Learning and Speaker Classifier Joint Training—0
Cross-speaker Style Transfer with Prosody Bottleneck in Neural Speech Synthesis—0
CrossSpeech++: Cross-lingual Speech Synthesis with Decoupled Language and Speaker Generation—0
CrossSpeech: Speaker-independent Acoustic Representation for Cross-lingual Speech Synthesis—0
Cross-Utterance Conditioned VAE for Speech Generation—0
Ctrl-P: Temporal Control of Prosodic Variation for Speech Synthesis—0
DART: Disentanglement of Accent and Speaker Representation in Multispeaker Text-to-Speech—0
DDOS: A MOS Prediction Framework utilizing Domain Adaptive Pre-training and Distribution of Opinion Scores—0
Debatts: Zero-Shot Debating Text-to-Speech Synthesis—0
Decoupled Pronunciation and Prosody Modeling in Meta-Learning-Based Multilingual Speech Synthesis—0
DeepA: A Deep Neural Analyzer For Speech And Singing Vocoding—0
Deep Denoising Auto-encoder for Statistical Speech Synthesis—0
Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis—0
Deep Feed-forward Sequential Memory Networks for Speech Synthesis—0
Deep Learning the EEG Manifold for Phonological Categorization from Active Thoughts—0
Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling—0
Deep Performer: Score-to-Audio Music Performance Synthesis—0
Deep Speech Synthesis from Articulatory Features—0
Deep Speech Synthesis from Multimodal Articulatory Representations—0
Deep Text-to-Speech System with Seq2Seq Model—0
Deliberation Networks and How to Train Them—0
De l'utilisation de descripteurs issus de la linguistique computationnelle dans le cadre de la synth\`ese par HMM (Toward the use of information density based descriptive features in HMM based speech synthesis)—0
Enhancing Word-Level Semantic Representation via Dependency Structure for Expressive Text-to-Speech Synthesis—0
Design and development a children's speech database—0
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All datasetsLibriTTSNorth American EnglishLJSpeechMandarin ChineseBlizzard Challenge 2013

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