| # Documentation Dataset: TTS_Multilingual_Data |
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| ## 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. |
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| ## Thematic Categories |
| Our dataset is organized into the following thematic categories. Please note that all audio files have a maximum duration of **20 seconds**. |
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| ### Speeches & Conferences |
| - "TED talk" |
| - "political speech" |
| - "interview" |
| - "podcast" |
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| ### Conversations & Dialogues |
| - "phone conversation" |
| - "spontaneous dialogue" |
| - "group discussion" |
| - "audio interview" |
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| ### Media Content & Entertainment |
| - "radio clip" |
| - "radio commentary" |
| - "audio narration" |
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| ### Instructions & Voice Assistants |
| - "voice commands" |
| - "voice assistant" |
| - "audio notification" |
| - "automated message" |
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| ### Informal Language & Common Expressions |
| - "slang" |
| - "French expressions" |
| - "colloquial language" |
| - "youth speech" |
| - "emotions in speech" |
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| ### Accessibility & Inclusion |
| - "speech with an accent" |
| - "elderly voices" |
| - "children speaking" |
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| ### Literature & Culture |
| - "literature" |
| - "tale" |
| - "fable" |
| - "poetry" |
| - "novel excerpt" |
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| ## 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. |
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| ## 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. |
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| ### 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). |
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| ## File Format |
| The dataset is delivered in **Parquet format**, optimized for efficient storage and processing. |
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| ## 8. Contact |
| For inquiries, please contact: |
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| - **Email**: [info@databoost.us](mailto\:info@databoost.us) |
| - **Website**: [databoost.us](https://databoost.us) |
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| ## Citations Information |
| If you use this dataset, please cite it as follows: |
| ```bibtex |
| @article{ |
| title={TTS_Multilingual_Data}, |
| author={Databoost}, |
| year={2025} |
| } |
