| | --- |
| | language: |
| | - fr |
| | --- |
| | # 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**. |
| |
|
| | ### Speeches & Conferences |
| | - "TED talk" |
| | - "political speech" |
| | - "interview" |
| | - "podcast" |
| |
|
| | ### Conversations & Dialogues |
| | - "phone conversation" |
| | - "spontaneous dialogue" |
| | - "group discussion" |
| | - "audio interview" |
| |
|
| | ### Media Content & Entertainment |
| | - "radio clip" |
| | - "radio commentary" |
| | - "audio narration" |
| |
|
| | ### Instructions & Voice Assistants |
| | - "voice commands" |
| | - "voice assistant" |
| | - "audio notification" |
| | - "automated message" |
| |
|
| | ### Informal Language & Common Expressions |
| | - "slang" |
| | - "French expressions" |
| | - "colloquial language" |
| | - "youth speech" |
| | - "emotions in speech" |
| |
|
| | ### Accessibility & Inclusion |
| | - "speech with an accent" |
| | - "elderly voices" |
| | - "children speaking" |
| |
|
| | ### Literature & Culture |
| | - "literature" |
| | - "tale" |
| | - "fable" |
| | - "poetry" |
| | - "novel excerpt" |
| |
|
| | ## 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} |
| | } |
