Create README.md

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:
+My dataset, TTS_Multilingual_Data, is organized as follows: at the root, there is a data folder containing two subfolders. The train folder includes data files in Parquet format (such as data1.parquet and data2.parquet), while the audio folder contains audio files in WAV format (for example, audio1.wav). At the root, a readme.md file provides details 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}
+}