Improving the Naturalness of Synthesized Spectrograms for TTS Using GAN-Based Post-Processing

This is the accompanying website for the following paper:

  1. Paolo Sani, Judith Bauer, Frank Zalkow, Emanuël A. P. Habets, and Christian Dittmar
    Improving the Naturalness of Synthesized Spectrograms for TTS Using GAN-Based Post-Processing
    In Proceedings of the ITG Conference on Speech Communication, 2023. Details DOI
    @inproceedings{SaniBZHD23_Postprocessing_ITG,
    author      = {Paolo Sani and Judith Bauer and Frank Zalkow and Emanu{\"e}l A.\ P.\ Habets and Christian Dittmar},
    title       = {Improving the Naturalness of Synthesized Spectrograms for {TTS} Using {GAN}-Based Post-Processing},
    booktitle   = {Proceedings of the {ITG} Conference on Speech Communication},
    address     = {Aachen, Germany},
    year        = {2023},
    pages       = {},
    doi         = {},
    url-pdf     = {},
    url-details = {https://www.audiolabs-erlangen.de/resources/NLUI/2023-ITG-postprocessing},
    }

Abstract

Recent text-to-speech (TTS) architectures usually synthesize speech in two stages. Firstly, an acoustic model predicts a compressed spectrogram from text input. Secondly, a neural vocoder converts the spectrogram into a time-domain audio signal. However, the synthesized spectrograms often substantially differ from real-world spectrograms. In particular, they miss fine-grained details, which is referred to as the “over-smoothing effect.” Consequently, the audio signals generated by the vocoder may contain audible artifacts. We propose a spectrogram post-processing model based on generative adversarial networks (GANs) to improve the naturalness of synthesized spectrograms. In our experiments, we use acoustic models of varying quality (yielding different degrees of artifacts) and conduct listening tests, which show that our approach can substantially improve the naturalness of synthesized spectrograms. This improvement is especially significant for highly degraded spectrograms, which miss fine-grained details or harmonic content.

Audio Samples

Here, we provide audio samples to illustrate the results of our paper. For a given ground-truth audio sample from the test set, we provide a reference obtained by copy synthesis (REF), the vocoded output from the acoustic model (RAW), and the vocoded result of our GAN-based post-processing model (GAN). We show the results for the four acoustic model versions considered in the paper, trained for 1k, 5k, 10k, and 300k iterations, respectively.

The audio samples are presented in an interactive web audio player, where you see two mel spectrograms along with the different audio conditions. The upper visualization always refers to the ground-truth spectrogram (obtained from the real recording, unlike REF obtained by copy synthesis) and the lower visualization refers to the respective audio condition that is currently selected.

For the demonstration purpose of this website, we selected three samples for each speaker of our multi-speaker TTS system. The table below lists the datasets that are the basis for the TTS system's speakers. Clicking on a dataset leads to the respective audio samples.

LJ Speech 1.1

Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition

speaker0_utterance0_ref

For although the Chinese took impressions from wood blocks engraved in relief for centuries before the woodcutters of the Netherlands, by a similar process

speaker0_utterance2_ref

the invention of movable metal letters in the middle of the fifteenth century may justly be considered as the invention of the art of printing.

speaker0_utterance4_ref

Hi-Fi TTS (speaker ID 92 only)

"How long have you been employed by the Embassy here?"

speaker1_utterance0_ref

You may not find another so favourable, so humane.

speaker1_utterance5_ref

After once more assuring the old woman on the threshold that she would know how to guard against the risk of Stevie losing himself for very long on his pilgrimages of filial piety,

speaker1_utterance7_ref

TC-STAR

As regards nitrogen levels, we would need reliable statistics and data from the various Member States.

speaker2_utterance0_ref

Mister President, the enumeration of the numbers of the amendments which could be accepted or not accepted, went tremendously quickly.

speaker2_utterance1_ref

Obviously, it is impossible to gloss over the tragic events which cast a pall over one of our Member States this summer.

speaker2_utterance2_ref

IIS Omondi Female

i want my men to work by themselves.

speaker3_utterance3_ref

nevertheless we found ourselves once more in the high seat of abundance.

speaker3_utterance8_ref

he did not know what went on in the minds of his superiors.

speaker3_utterance9_ref

IIS Omondi Male

i want my men to work by themselves.

speaker4_utterance3_ref

nevertheless we found ourselves once more in the high seat of abundance.

speaker4_utterance8_ref

he did not know what went on in the minds of his superiors.

speaker4_utterance9_ref

Acknowledgements

We thank all participants of our listening test. Parts of this work have been supported by the SPEAKER project (FKZ 01MK20011A), funded by the German Federal Ministry for Economic Affairs and Climate Action. In addition, this work was supported by the Free State of Bavaria in the DSAI project. The International Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Fraunhofer Institute for Integrated Circuits IIS. The authors gratefully acknowledge the technical support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the FAU.

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