African Kikuyu TTS EU AI Act Compliance Profile

African Kikuyu Text-to-Speech Model

Model Description

This is a Text-to-Speech (TTS) model for the Kikuyu language, one of the major languages spoken in Kenya. The model is based on Facebook's Massively Multilingual Speech (MMS) project and has been redeployed here for better discoverability and accessibility.

Language Information

• Language: Kikuyu (Gĩkũyũ)
• Language Code: ki (ISO 639-1), kik (ISO 639-3)
• Family: Niger-Congo, Atlantic-Congo, Volta-Congo, Benue-Congo, Bantoid, Southern, Narrow Bantu, Central, J, Kikuyu-Kamba (J.10)
• Speakers: Approximately 8.1 million native speakers
• Region: Central Kenya

Model Details

• Model Type: VITS (Variational Inference with adversarial learning for end-to-end Text-to-Speech)
• Base Model: facebook/mms-tts-kik
• Training Data: Part of Facebook's MMS dataset
• Supported Task: Text-to-Speech synthesis for Kikuyu language

Usage

Using Transformers

from transformers import VitsModel, VitsTokenizer
import torch
import scipy.io.wavfile
import numpy as np

# Load model and tokenizer
model = VitsModel.from_pretrained("BrianMwangi/African-Kikuyu-TTS")
tokenizer = VitsTokenizer.from_pretrained("BrianMwangi/African-Kikuyu-TTS")

# Example text in Kikuyu
text = "Mũthenya ũmwe, njũgũ ya ita yakoragwo na atumia a njũri cia kĩrĩra"

# Generate speech
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)

# Save audio file
audio = outputs.waveform.squeeze().cpu().numpy()
scipy.io.wavfile.write("kikuyu_speech.wav", rate=model.config.sampling_rate, data=audio)

Using Pipeline

from transformers import pipeline

# Create TTS pipeline
tts = pipeline("text-to-speech", model="BrianMwangi/African-Kikuyu-TTS")

# Generate speech
speech = tts("Mũthenya ũmwe, njũgũ ya ita yakoragwo na atumia a njũri cia kĩrĩra")

Examples

Here are some example phrases in Kikuyu:

• "Wĩ mwega" - "You are good"
• **"N

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