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| 1 |
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Nigerian Text-to-Speech API
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This is a API service that converts text to speech with authentic Nigerian accents. The API is built with FastAPI and uses the YarnGPT text-to-speech model.
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Features
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Convert text to Nigerian-accented speech
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Multiple voices and languages
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REST API endpoints
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Base64 encoded audio output
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Simple file-based output
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API Endpoints
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Health Check
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URL: /
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Method: GET
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Response: Information about the API status and available voices/languages
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Text-to-Speech
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URL: /tts
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Method: POST
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Body:
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json{
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"text": "Your text to convert to speech",
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"language": "english",
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"voice": "idera",
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"speed": 1.0
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}
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Response: JSON object with base64-encoded audio and audio URL
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Get Audio File
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URL: /audio/{filename}
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Method: GET
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Response: Audio file (WAV format)
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Usage Examples
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cURL Example
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bashcurl -X POST "https://yourdomain.com/tts" \
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-H "Content-Type: application/json" \
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-d '{"text":"Welcome to Nigeria, the giant of Africa.", "language":"english", "voice":"idera"}'
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Python Example
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pythonimport requests
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import base64
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import io
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from IPython.display import Audio
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response = requests.post(
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"https://yourdomain.com/tts",
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json={
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"text": "Welcome to Nigeria, the giant of Africa.",
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"language": "english",
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"voice": "idera",
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"speed": 1.0
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}
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)
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data = response.json()
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audio_data = base64.b64decode(data["audio_base64"])
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Audio(audio_data, rate=24000)
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Available Voices and Languages
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Voices
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Female: zainab, idera, regina, chinenye, joke, remi
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Male: jude, tayo, umar, osagie, onye, emma
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Languages
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english
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yoruba
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igbo
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hausa
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Configuration
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The API uses the following YarnGPT model:
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Model: yarngpt/yarn-tts-demo
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Deployment
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This API is designed to run on Hugging Face Spaces with the following configuration:
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SDK: Docker
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Hardware: CPU (recommended: GPU for better performance)
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