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-# 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., data1.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**: [info@databoost.us](mailto\:info@databoost.us)
-- **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}
-}