| # Documentation Dataset: TTS_Multilingual_Data | |
| ## Dataset Summary | |
| This large-scale multilingual corpus is designed for linguistic analysis and the development of speech processing models. It supports tasks such as **Text-to-Speech (TTS)**, **Automatic Speech Recognition (ASR)**, and **speaker identification**. Structured in **Parquet format**, it serves as a key resource for training and evaluating models, using metrics tailored to ASR and speech technologies. | |
| ## Thematic Categories | |
| Our dataset is organized into the following thematic categories. Please note that all audio files have a maximum duration of **20 seconds**. | |
| ### Discours & Conférences | |
| - "conférence TED" | |
| - "discours politique" | |
| - "interview" | |
| - "podcast" | |
| ### Conversations & Dialogues | |
| - "conversation téléphonique" | |
| - "dialogue spontané" | |
| - "discussion en groupe" | |
| - "interview audio" | |
| ### Contenus Médias & Divertissement | |
| - "extrait de radio" | |
| - "chronique radio" | |
| - "narration audio" | |
| ### Instructions & Assistants Vocaux | |
| - "commandes vocales" | |
| - "assistant vocal" | |
| - "notification audio" | |
| - "message automatique" | |
| ### Langage Informel & Expressions Courantes | |
| - "argot" | |
| - "expressions françaises" | |
| - "langage familier" | |
| - "parler jeune" | |
| - "émotions en parole" | |
| ### Accessibilité & Inclusion | |
| - "parole avec accent" | |
| - "voix de personnes âgées" | |
| - "enfants qui parlent" | |
| ### Littérature & Culture | |
| - "littérature" | |
| - "conte" | |
| - "fable" | |
| - "poésie" | |
| - "extrait de roman" | |
| ## Supported Tasks | |
| - **Text-to-Speech (TTS)**: The dataset can be used to train models for generating speech from text. | |
| - **Automatic Speech Recognition (ASR)**: The dataset can be used to train models for transcribing speech to text. The most common evaluation metric is the **Word Error Rate (WER)**. | |
| - **Speaker Identification**: The dataset supports tasks related to identifying speakers based on their voice. | |
| ## Dataset Structure | |
| ### Organisation of the Project | |
| The dataset, **TTS_Multilingual_Data**, is organized as follows: | |
| containing one subfolder. The train subfolder includes data files in Parquet format (e.g., data.parquet), while the audio subfolder contains audio files in WAV format (e.g., audio1.wav). Additionally, a readme.md file at the root level provides detailed information about the dataset's content and usage. | |
| ### Columns | |
| - **audio_path** (string): Path to the audio file. | |
| - **text** (string): Ground truth transcription. | |
| - **duration** (float64): Duration of the audio file in seconds. | |
| - **speaker_id** (string or int): Identifier for the speaker. | |
| - **audio_format** (string): Format of the audio file (e.g., WAV, MP3). | |
| - **sampling_rate** (int): Sampling rate of the audio file. | |
| - **language** (string): Language of the transcription. | |
| - **gender** (string): Gender of the speaker (if available). | |
| ## File Format | |
| The dataset is delivered in **Parquet format**, optimized for efficient storage and processing. | |
| ## 8. Contact | |
| For inquiries, please contact: | |
| - **Email**: [[email protected]](mailto\:[email protected]) | |
| - **Website**: [databoost.us](https://databoost.us) | |
| ## Citations Information | |
| If you use this dataset, please cite it as follows: | |
| ```bibtex | |
| @article{ | |
| title={TTS_Multilingual_Data}, | |
| author={Databoost}, | |
| year={2025} | |
| } | |