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# Documentation Dataset: TTS_Multilingual_Data |
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## Dataset Summary |
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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 |
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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 |
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- "TED talk" |
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- "political speech" |
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- "interview" |
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- "podcast" |
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### Conversations & Dialogues |
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- "phone conversation" |
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- "spontaneous dialogue" |
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- "group discussion" |
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- "audio interview" |
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### Media Content & Entertainment |
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- "radio clip" |
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- "radio commentary" |
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- "audio narration" |
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### Instructions & Voice Assistants |
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- "voice commands" |
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- "voice assistant" |
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- "audio notification" |
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- "automated message" |
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### Informal Language & Common Expressions |
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- "slang" |
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- "French expressions" |
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- "colloquial language" |
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- "youth speech" |
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- "emotions in speech" |
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### Accessibility & Inclusion |
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- "speech with an accent" |
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- "elderly voices" |
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- "children speaking" |
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### Literature & Culture |
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- "literature" |
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- "tale" |
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- "fable" |
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- "poetry" |
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- "novel excerpt" |
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## Supported Tasks |
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- **Text-to-Speech (TTS)**: The dataset can be used to train models for generating speech from text. |
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- **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)**. |
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- **Speaker Identification**: The dataset supports tasks related to identifying speakers based on their voice. |
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## Dataset Structure |
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### Organisation of the Project |
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The dataset, **TTS_Multilingual_Data**, is organized as follows: |
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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 |
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- **audio_path** (string): Path to the audio file. |
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- **text** (string): Ground truth transcription. |
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- **duration** (float64): Duration of the audio file in seconds. |
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- **speaker_id** (string or int): Identifier for the speaker. |
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- **audio_format** (string): Format of the audio file (e.g., WAV, MP3). |
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- **sampling_rate** (int): Sampling rate of the audio file. |
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- **language** (string): Language of the transcription. |
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- **gender** (string): Gender of the speaker (if available). |
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## File Format |
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The dataset is delivered in **Parquet format**, optimized for efficient storage and processing. |
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## 8. Contact |
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For inquiries, please contact: |
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- **Email**: [[email protected]](mailto\:[email protected]) |
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- **Website**: [databoost.us](https://databoost.us) |
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## Citations Information |
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If you use this dataset, please cite it as follows: |
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```bibtex |
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@article{ |
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title={TTS_Multilingual_Data}, |
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author={Databoost}, |
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year={2025} |
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} |