nigerian-accent-english

Nigerian Accent English TTS — XTTS v2

A fine-tuned XTTS v2 model specialized for Nigerian-accented English text-to-speech synthesis with zero-shot voice cloning.

Given a short reference audio clip of any English speaker with a Nigerian accent, the model synthesizes any English text in that voice — preserving the natural Nigerian accent, rhythm, and prosody.

Model Details

Capabilities

• Synthesize natural English speech with an authentic Nigerian accent
• Clone any Nigerian-accented English voice from a short reference clip (~6 seconds)
• Preserve the speaker's unique tone, rhythm, and accent characteristics
• Suitable for Nigerian media, education, accessibility, and voice applications

Installation

pip install TTS

Usage

Simple voice cloning

from TTS.api import TTS

tts = TTS("yusasif/nigerian-accent-english", gpu=True)

tts.tts_to_file(
    text="Welcome to Nigeria. How can I assist you today?",
    file_path="output.wav",
    speaker_wav="reference_speaker.wav",  # ~6 seconds of clean Nigerian-accented English
    language="en",
)

Low-level API for more control

from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.models.xtts import Xtts
import soundfile as sf

config = XttsConfig()
config.load_json("/path/to/model/config.json")
model = Xtts.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="/path/to/model/", eval=True)
model.cuda()

# Extract voice characteristics from reference audio
gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(
    audio_path="reference_speaker.wav"
)

# Synthesize
outputs = model.inference(
    text="Welcome to Nigeria. How can I assist you today?",
    language="en",
    gpt_cond_latent=gpt_cond_latent,
    speaker_embedding=speaker_embedding,
    temperature=0.7,
    speed=1.0,
)

sf.write("output.wav", outputs["wav"], 24000)

Tips for Best Results

• Use 6–12 seconds of clean, noise-free reference audio for best voice cloning
• The reference audio should be recorded in a quiet environment
• The model captures Nigerian accent most accurately when the reference speaker also has a Nigerian accent
• Avoid reference clips with background music or heavy noise

Reference Voice Guidelines