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README.md

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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}
+}