Browse State-of-the-Art › Speech Synthesis
Speech Synthesis
366 papers with code · 5 benchmarks · 22 datasets archive 2025-07-28
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 )
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| LibriTTS (15 rows) | PeriodWave-Turbo-L | Accelerating High-Fidelity Waveform Generation via Adversarial... | code | — | Compare |
| North American English (7 rows) | Tacotron 2 | Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram... | code | Syntology ran 7 of 7 samples · 0 unverified | Compare |
| LJSpeech (4 rows) | BDDM vocoder | BDDM: Bilateral Denoising Diffusion Models for Fast and... | code | Syntology ran 5 of 6 samples · 1 unverified | Compare |
| Mandarin Chinese (3 rows) | WaveNet (L+F) | WaveNet: A Generative Model for Raw Audio | code | Syntology ran 41 of 103 samples · 62 unverified | Compare |
| Blizzard Challenge 2013 (2 rows) | SampleRNN (3-tier) | SampleRNN: An Unconditional End-to-End Neural Audio Generation Model | code | Syntology ran 0 of 11 samples · 11 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
22 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
15 subtasks in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 366 papers with code (1,249 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
12 Sep 2016 62 repositories listed Syntology ran 41 of 103 samples · 62 unverified · 25 pointer-only (licence)This paper introduces WaveNet, a deep neural network for generating raw audio waveforms.
-
8 Jun 2020 37 repositories listed Syntology ran 73 of 119 samples · 46 unverified · 33 pointer-only (licence)In this paper, we propose FastSpeech 2, which addresses the issues in FastSpeech and better solves the one-to-many mapping problem in TTS by 1) directly training the model with ground-truth target instead of the…
-
16 Dec 2017 33 repositories listed Syntology ran 7 of 7 samples · 0 unverified · 2 pointer-only (licence)This paper describes Tacotron 2, a neural network architecture for speech synthesis directly from text.
-
29 Mar 2017 30 repositories listed Syntology ran 7 of 25 samples · 18 unverified · 6 pointer-only (licence)A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module.
-
22 May 2019 22 repositories listed Syntology ran 3 of 11 samples · 8 unverified · 3 pointer-only (licence)In this work, we propose a novel feed-forward network based on Transformer to generate mel-spectrogram in parallel for TTS.
-
8 Oct 2019 21 repositories listed Syntology ran 5 of 7 samples · 2 unverified · 1 pointer-only (licence)In this paper, we show that it is possible to train GANs reliably to generate high quality coherent waveforms by introducing a set of architectural changes and simple training techniques.
-
23 Feb 2018 16 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)The small number of weights in a Sparse WaveRNN makes it possible to sample high-fidelity audio on a mobile CPU in real time.
-
25 Oct 2019 12 repositories listed Syntology ran 0 of 20 samples · 20 unverified · 1 pointer-only (licence)We propose Parallel WaveGAN, a distillation-free, fast, and small-footprint waveform generation method using a generative adversarial network.
-
12 Oct 2020 11 repositories listed Syntology ran 17 of 25 samples · 8 unverified · 3 pointer-only (licence)Several recent work on speech synthesis have employed generative adversarial networks (GANs) to produce raw waveforms.
-
21 Sep 2020 11 repositories listed Syntology ran 20 of 33 samples · 13 unverifiedIn this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional and unconditional waveform generation.
-
12 Jun 2018 11 repositories listedClone a voice in 5 seconds to generate arbitrary speech in real-time
-
23 Mar 2018 11 repositories listed Syntology ran 6 of 21 samples · 15 unverified · 7 pointer-only (licence)In this work, we propose "global style tokens" (GSTs), a bank of embeddings that are jointly trained within Tacotron, a state-of-the-art end-to-end speech synthesis system.
-
15 Jun 2021 9 repositories listed Syntology ran 8 of 12 samples · 4 unverified · 1 pointer-only (licence)Using full-band mel-spectrograms as input, we expect to generate high-resolution signals by adding a discriminator that employs spectrograms of multiple resolutions as the input.
-
5 Jan 2023 7 repositories listed Syntology ran 6 of 6 samples · 0 unverifiedIn addition, we find Vall-E could preserve the speaker's emotion and acoustic environment of the acoustic prompt in synthesis.
-
2 Sep 2020 7 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 1 pointer-only (licence)This paper introduces WaveGrad, a conditional model for waveform generation which estimates gradients of the data density.
-
20 Oct 2017 7 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)We present Deep Voice 3, a fully-convolutional attention-based neural text-to-speech (TTS) system.
-
14 Oct 2021 6 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural language processing models, we propose a unified-modal SpeechT5 framework that explores the encoder-decoder pre-training for…
-
13 May 2021 6 repositories listed Syntology ran 9 of 18 samples · 9 unverified · 1 pointer-only (licence)Recently, denoising diffusion probabilistic models and generative score matching have shown high potential in modelling complex data distributions while stochastic calculus has provided a unified point of view on these…
-
4 Sep 2019 6 repositories listedIn this paper, we present a generic and robust multimodal synthesis system that produces highly natural speech and facial expression simultaneously.
-
19 Sep 2018 6 repositories listedAlthough end-to-end neural text-to-speech (TTS) methods (such as Tacotron2) are proposed and achieve state-of-the-art performance, they still suffer from two problems: 1) low efficiency during training and inference; 2)…
-
3 Apr 2018 6 repositories listed Syntology ran 3 of 8 samples · 5 unverified · 2 pointer-only (licence)Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to accelerate state-of-the-art…
-
9 Jun 2022 5 repositories listed Syntology ran 8 of 17 samples · 9 unverified · 1 pointer-only (licence)Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthesize high-fidelity audio for numerous…
-
4 Jun 2019 5 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)Capturing high-level structure in audio waveforms is challenging because a single second of audio spans tens of thousands of timesteps.
-
14 Jan 2019 5 repositories listedDuring the last few years, spoken language technologies have known a big improvement thanks to Deep Learning.
-
19 Jul 2018 5 repositories listed Syntology ran 1 of 13 samples · 12 unverifiedIn this work, we propose a new solution for parallel wave generation by WaveNet.
-
23 Sep 2017 5 repositories listedIn the proposed framework incorporating the GANs, the discriminator is trained to distinguish natural and generated speech parameters, while the acoustic models are trained to minimize the weighted sum of the…
-
13 Jul 2024 4 repositories listedIt is too early to conclude that Mamba is a better alternative to transformers for speech before comparing Mamba with transformers in terms of both performance and efficiency in multiple speech-related tasks.
-
1 Jun 2023 4 repositories listed Syntology ran 5 of 16 samples · 11 unverifiedRecent advancements in neural vocoding are predominantly driven by Generative Adversarial Networks (GANs) operating in the time-domain.
-
22 May 2023 4 repositories listed Syntology ran 3 of 3 samples · 0 unverifiedExpanding the language coverage of speech technology has the potential to improve access to information for many more people.
-
13 Jul 2022 4 repositories listed Syntology ran 2 of 6 samples · 4 unverifiedThrough the preliminary study on diffusion model parameterization, we find that previous gradient-based TTS models require hundreds or thousands of iterations to guarantee high sample quality, which poses a challenge…
Syntology lines on 24 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections