| | --- |
| | dataset_info: |
| | features: |
| | - name: audio |
| | dtype: |
| | audio: |
| | sampling_rate: 16000 |
| | - name: text |
| | dtype: string |
| | - name: speaker_id |
| | dtype: string |
| | - name: gender |
| | dtype: string |
| | - name: language |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 34233764350.525497 |
| | num_examples: 30182 |
| | - name: test |
| | num_bytes: 2997327619.754504 |
| | num_examples: 3356 |
| | download_size: 23038211822 |
| | dataset_size: 37231091970.28 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | - split: test |
| | path: data/test-* |
| | --- |
| | |
| | <h1 align="center">VoTexUg-TTS dataset</h1> |
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| | <p align="center"> |
| | <img |
| | src="https://cdn-uploads.huggingface.co/production/uploads/634a8bd029bfb408244fe4dd/grOdNhiTkmzrcwGxScIxV.png" |
| | width="500" |
| | alt="Gender distribution visualization" |
| | /> |
| | </p> |
| |
|
| | VoTexUg-TTS is a large-scale multilingual text-to-speech (TTS) dataset designed to support the development of high-quality speech synthesis models for widely spoken Ugandan languages. The dataset emphasizes linguistic diversity, gender balance, and natural African accents, addressing the persistent underrepresentation of African languages in speech technologies. |
| |
|
| | ## Dataset Details |
| |
|
| | ### Dataset Description |
| |
|
| | The VoTexUg-TTS dataset contains approximately **68 hours of studio-quality speech audio** paired with text transcriptions. Data was collected by **12 students from Soroti University** using a **custom-built recording and upload system**, ensuring consistency in audio quality and metadata capture. Each audio sample is sampled at **16 kHz** and annotated with speaker identity, gender, and language. |
| |
|
| | To promote **gender diversity**, each of the six languages in the dataset is represented by **two speakers (one male and one female)**. All recordings were reviewed and either approved or rejected through a structured quality assurance process before inclusion. |
| |
|
| | - **Curated by:** Kisejjere Rashid, Magala Reuben, Lynn Tar Gutu, Abubakhari Sserwadda |
| | - **Funded by:** Soroti University Research and Innovation Fund (SUNRIF) |
| | https://sun.ac.ug/in-the-press/research-funds-call-for-proposals/ |
| | - **Shared by:** Soroti University |
| | - **Language(s) (NLP):** English, Lusoga, Luganda, Runyankole, Acholi, Atteso |
| | - **License:** More Information Needed |
| |
|
| | ### Dataset Sources |
| |
|
| | - **Repository:** More Information Needed |
| | - **Paper:** More Information Needed |
| | - **Demo:** More Information Needed |
| |
|
| | ## Uses |
| |
|
| | ### Direct Use |
| |
|
| | The dataset is intended for: |
| | - Training and fine-tuning **text-to-speech (TTS) models** |
| | - Research on **multilingual and low-resource speech synthesis** |
| | - Accent-aware and **African English speech generation** |
| | - Speaker-conditioned and gender-aware TTS systems |
| |
|
| | ### Out-of-Scope Use |
| |
|
| | The dataset is **not suitable** for: |
| | - Speaker identification or biometric surveillance |
| | - Emotion recognition tasks (emotions are not explicitly annotated) |
| | - Automatic speech recognition (ASR) benchmarking without adaptation |
| | - Any application involving impersonation or deceptive voice cloning |
| |
|
| | ## Dataset Structure |
| |
|
| | Each data sample consists of: |
| | - `audio`: Speech waveform (16 kHz) |
| | - `text`: Corresponding transcription |
| | - `speaker_id`: Unique speaker identifier |
| | - `gender`: Speaker gender (male or female) |
| | - `language`: One of the six supported languages |
| |
|
| | The dataset is split into **train** and **test** sets. Splits were created to maintain balance across languages and genders. |
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| |  |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | The dataset was created to address the scarcity of high-quality TTS resources for Ugandan and African languages, and to enable the development of **realistic voice generation models with authentic African accents**. |
| |
|
| | ### Source Data |
| |
|
| | #### Data Collection and Processing |
| |
|
| | - A **custom-designed web-based recording system** was developed for the project |
| | - Students recorded and uploaded speech data directly through the system |
| | - Each submission underwent **manual review and validation** |
| | - Recordings not meeting quality standards were rejected |
| | - Accepted data was normalized and structured into standardized splits |
| |
|
| | #### Who are the source data producers? |
| |
|
| | The source data was produced by **12 student contributors from Soroti University**, selected to represent native or fluent speakers of the target languages. Basic demographic metadata (language and gender) was collected; no personally identifiable information is included. |
| |
|
| | ### Annotations |
| |
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| | #### Annotation process |
| |
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| | Annotations include text transcriptions and speaker metadata (language, gender, speaker ID). Annotation and validation were carried out during the review stage using the custom system. No emotion or prosodic labels are provided. |
| |
|
| | #### Who are the annotators? |
| |
|
| | The annotations and quality reviews were performed by the project leads and designated reviewers from the Soroti University research team. |
| |
|
| | #### Personal and Sensitive Information |
| |
|
| | The dataset does **not contain sensitive personal information**. Speaker identities are anonymized using speaker IDs, and no names, addresses, or contact details are included. |
| |
|
| | ## Bias, Risks, and Limitations |
| |
|
| | - Limited number of speakers per language (two per language) |
| | - Accents may reflect regional or educational backgrounds of student speakers |
| | - Not all Ugandan languages are represented |
| | - Dataset size may limit generalization for very large TTS models |
| |
|
| | ### Recommendations |
| |
|
| | Users should be aware of potential linguistic and demographic biases and are encouraged to: |
| | - Combine this dataset with other African speech resources where possible |
| | - Avoid misuse for identity inference or voice impersonation |
| | - Clearly state dataset limitations when publishing results |
| |
|
| | ## Glossary |
| |
|
| | - **TTS:** Text-to-Speech |
| | - **Low-resource languages:** Languages with limited digital and annotated data |
| |
|
| | ## Dataset Card Authors |
| |
|
| | Kisejjere Rashid, Magala Reuben, Lynn Tar Gutu, Abubakhari Sserwadda |
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