--- dataset_info: - config_name: dutch features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: sdr_noise dtype: string - name: pesq_speech_quality dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 239921852 num_examples: 231177 - name: dev num_bytes: 1787744 num_examples: 1641 - name: test num_bytes: 1766102 num_examples: 1661 download_size: 108495579 dataset_size: 243475698 - config_name: french features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: sdr_noise dtype: string - name: pesq_speech_quality dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 109864516 num_examples: 99997 - name: dev num_bytes: 2438561 num_examples: 2293 - name: test num_bytes: 2540344 num_examples: 2378 download_size: 53314347 dataset_size: 114843421 - config_name: german features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: sdr_noise dtype: string - name: pesq_speech_quality dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 562200669 num_examples: 527484 - name: dev num_bytes: 4014971 num_examples: 3628 - name: test num_bytes: 3906399 num_examples: 3592 download_size: 256582021 dataset_size: 570122039 - config_name: italian features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: sdr_noise dtype: string - name: pesq_speech_quality dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 50694410 num_examples: 47133 - name: dev num_bytes: 787099 num_examples: 786 - name: test num_bytes: 940716 num_examples: 958 download_size: 24588039 dataset_size: 52422225 - config_name: polish features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 16459590 num_examples: 15136 - name: dev num_bytes: 559635 num_examples: 564 - name: test num_bytes: 649740 num_examples: 603 download_size: 9411733 dataset_size: 17668965 - config_name: portuguese features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: stoi dtype: float64 - name: si-sdr dtype: float64 - name: pesq dtype: float64 - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: sdr_noise dtype: string - name: pesq_speech_quality dtype: string - name: text_description dtype: string splits: - name: train num_bytes: 22702074 num_examples: 25732 - name: dev num_bytes: 300602 num_examples: 352 - name: test num_bytes: 204377 num_examples: 265 download_size: 11573093 dataset_size: 23207053 - config_name: spanish features: - name: wav_filesize dtype: int64 - name: text dtype: string - name: transcript_wav2vec dtype: string - name: levenshtein dtype: float64 - name: duration dtype: float64 - name: num_words dtype: int64 - name: speaker_id dtype: int64 - name: utterance_pitch_mean dtype: float32 - name: utterance_pitch_std dtype: float32 - name: snr dtype: float64 - name: c50 dtype: float64 - name: speaking_rate dtype: string - name: phonemes dtype: string - name: original_text dtype: string - name: gender dtype: string - name: pitch dtype: string - name: noise dtype: string - name: reverberation dtype: string - name: speech_monotony dtype: string - name: text_description dtype: string - name: original_text_description dtype: string splits: - name: train num_bytes: 159210207 num_examples: 153150 - name: dev num_bytes: 2007744 num_examples: 1897 - name: test num_bytes: 1731824 num_examples: 1662 download_size: 79579984 dataset_size: 162949775 configs: - config_name: dutch data_files: - split: train path: dutch/train-* - split: dev path: dutch/dev-* - split: test path: dutch/test-* - config_name: french data_files: - split: train path: french/train-* - split: dev path: french/dev-* - split: test path: french/test-* - config_name: german data_files: - split: train path: german/train-* - split: dev path: german/dev-* - split: test path: german/test-* - config_name: italian data_files: - split: train path: italian/train-* - split: dev path: italian/dev-* - split: test path: italian/test-* - config_name: polish data_files: - split: train path: polish/train-* - split: dev path: polish/dev-* - split: test path: polish/test-* - config_name: portuguese data_files: - split: train path: portuguese/train-* - split: dev path: portuguese/dev-* - split: test path: portuguese/test-* - config_name: spanish data_files: - split: train path: spanish/train-* - split: dev path: spanish/dev-* - split: test path: spanish/test-* license: cc-by-4.0 task_categories: - text-to-speech language: - fr - de - it - es - pl - pt - nl --- # Dataset Card for Filtred and annotated CML TTS **This dataset is an annotated and filtred version of a [CML-TTS](https://huggingface.co/datasets/ylacombe/cml-tts) [1].** [CML-TTS](https://huggingface.co/datasets/ylacombe/cml-tts) [1] CML-TTS is a recursive acronym for CML-Multi-Lingual-TTS, a Text-to-Speech (TTS) dataset developed at the Center of Excellence in Artificial Intelligence (CEIA) of the Federal University of Goias (UFG). CML-TTS is a dataset comprising audiobooks sourced from the public domain books of Project Gutenberg, read by volunteers from the LibriVox project. The dataset includes recordings in Dutch, German, French, Italian, Polish, Portuguese, and Spanish, all at a sampling rate of 24kHz. The [original dataset](https://huggingface.co/datasets/ylacombe/cml-tts) has been [cleaned](https://huggingface.co/datasets/PHBJT/cml-tts-filtered) by removing all rows with a Levenshtein score inferior to 0.9. In the `text_description` column, it provides natural language annotations on the characteristics of speakers and utterances, that have been generated using [the Data-Speech repository](https://github.com/huggingface/dataspeech). This dataset was used alongside the [LibriTTS-R English dataset](https://huggingface.co/datasets/blabble-io/libritts_r) and the [Non English subset of MLS](https://huggingface.co/datasets/facebook/multilingual_librispeech) to train [Parler-TTS Multilingual [Mini v1.1](https://huggingface.co/ylacombe/p-m-e). A training recipe is available in [the Parler-TTS library](https://github.com/huggingface/parler-tts). ## Motivation This dataset is a reproduction of work from the paper [Natural language guidance of high-fidelity text-to-speech with synthetic annotations](https://www.text-description-to-speech.com) by Dan Lyth and Simon King, from Stability AI and Edinburgh University respectively. It was designed to fine tune the Parler-TTS [Mini v1.1]((https://huggingface.co/parler-tts/parler-tts-mini-v1)) on 8 european languages (including English). Contrarily to other TTS models, Parler-TTS is a **fully open-source** release. All of the datasets, pre-processing, training code and weights are released publicly under permissive license, enabling the community to build on our work and develop their own powerful TTS models. Parler-TTS was released alongside: * [The Parler-TTS repository](https://github.com/huggingface/parler-tts) - you can train and fine-tuned your own version of the model. * [The Data-Speech repository](https://github.com/huggingface/dataspeech) - a suite of utility scripts designed to annotate speech datasets. * [The Parler-TTS organization](https://huggingface.co/parler-tts) - where you can find the annotated datasets as well as the future checkpoints. ## Usage Here is an example on how to oad the `clean` config with only the `train.clean.360` split. ```py from datasets import load_dataset load_dataset("https://huggingface.co/datasets/PHBJT/cml-tts-filtered", "french", split="train") ``` **Note:** This dataset doesn't actually keep track of the audio column of the original version. You can merge it back to the original dataset using [this script](https://github.com/huggingface/dataspeech/blob/main/scripts/merge_audio_to_metadata.py) from Parler-TTS or, even better, get inspiration from [the training script](https://github.com/huggingface/parler-tts/blob/main/training/run_parler_tts_training.py) of Parler-TTS, that efficiently process multiple annotated datasets. You can find the original dataset [here](https://huggingface.co/datasets/PHBJT/cml-tts-filtered) ### Dataset Description - **License:** CC BY 4.0 ### Dataset Sources - **Homepage:** https://www.openslr.org/141/ - **Paper:** https://arxiv.org/abs/2305.18802 ## Citation ``` @misc{oliveira2023cmltts, title={CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages}, author={Frederico S. Oliveira and Edresson Casanova and Arnaldo Cândido Júnior and Anderson S. Soares and Arlindo R. Galvão Filho}, year={2023}, eprint={2306.10097}, archivePrefix={arXiv}, primaryClass={eess.AS} } ``` ``` @misc{lacombe-etal-2024-dataspeech, author = {Yoach Lacombe and Vaibhav Srivastav and Sanchit Gandhi}, title = {Data-Speech}, year = {2024}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/ylacombe/dataspeech}} } ``` ``` @misc{lyth2024natural, title={Natural language guidance of high-fidelity text-to-speech with synthetic annotations}, author={Dan Lyth and Simon King}, year={2024}, eprint={2402.01912}, archivePrefix={arXiv}, primaryClass={cs.SD} } ```