From 3ece0c49c34999f234cf668c52de4a5b9d5a2968 Mon Sep 17 00:00:00 2001
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-[](https://discourse.mozilla.org/c/tts)
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This project is a part of [Mozilla Common Voice](https://voice.mozilla.org/en). TTS aims a deep learning based Text2Speech engine, low in cost and high in quality.
From c1d3b2a079d0be7a84833ce8d5572c6594760722 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Eren=20G=C3=B6lge?=
Date: Wed, 15 Jul 2020 11:14:46 +0200
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-This project is a part of [Mozilla Common Voice](https://voice.mozilla.org/en). TTS aims a deep learning based Text2Speech engine, low in cost and high in quality.
+This project is a part of [Mozilla Common Voice](https://voice.mozilla.org/en).
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+Mozilla TTS aims a deep learning based Text2Speech engine, low in cost and high in quality.
You can check some of synthesized voice samples from [here](https://erogol.github.io/ddc-samples/).
From fb406d6e4d95bda4d9a67162879a1f094dbccad7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Eren=20G=C3=B6lge?=
Date: Wed, 15 Jul 2020 11:15:26 +0200
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You can also enjoy Tensorboard, if you point Tensorboard argument```--logdir``` to the experiment folder.
-## [Testing and Examples](https://github.com/mozilla/TTS/wiki/Examples-using-TTS)
-
## Contribution guidelines
This repository is governed by Mozilla's code of conduct and etiquette guidelines. For more details, please read the [Mozilla Community Participation Guidelines.](https://www.mozilla.org/about/governance/policies/participation/)
From f9c36bbf3260de353e8ace46c0a1087d00536aa0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Eren=20G=C3=B6lge?=
Date: Wed, 15 Jul 2020 11:20:23 +0200
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## [Mozilla TTS Tutorials and Notebooks](https://github.com/mozilla/TTS/wiki/TTS-Notebooks-and-Tutorials)
## Datasets and Data-Loading
-TTS provides a generic dataloader easy to use for new datasets. You need to write an preprocessor function to integrate your own dataset.Check ```datasets/preprocess.py``` to see some examples. After the function, you need to set ```dataset``` field in ```config.json```. Do not forget other data related fields too.
+TTS provides a generic dataloader easy to use for your custom dataset.
+You just need to write a simple function to format the dataset. Check ```datasets/preprocess.py``` to see some examples.
+After that, you need to set ```dataset``` fields in ```config.json```.
-Some of the open-sourced datasets that we successfully applied TTS, are linked below.
+Some of the public datasets that we successfully applied TTS:
- [LJ Speech](https://keithito.com/LJ-Speech-Dataset/)
- [Nancy](http://www.cstr.ed.ac.uk/projects/blizzard/2011/lessac_blizzard2011/)