Swahili female voice text-to-speech model

This is a continuous development of text-to-speech model for female voice using Swahili language

Please give it a try

for inference try the following

# import all required libraries
from transformers import VitsModel, AutoTokenizer
import torch
import numpy as np
import scipy.io.wavfile

# Load model and tokenizer
model = VitsModel.from_pretrained("mussacharles60/swahili-tts-female-voice")
tokenizer = AutoTokenizer.from_pretrained("mussacharles60/swahili-tts-female-voice")

# Running the TTS
text = "Mambo vipi ?, Hii ni Myssa Tech sauti ya A.I, kujaribishwa na Mussa Charles"
inputs = tokenizer(text, return_tensors="pt")

# Generate waveform
with torch.no_grad():
    output = model(**inputs).waveform

# Convert PyTorch tensor to NumPy array
output_np = output.squeeze().cpu().numpy()

# Write to WAV file
scipy.io.wavfile.write("female_voice_test.wav", rate=model.config.sampling_rate, data=output_np)

You're all welcome to contribute.

Thanks 🤗

Downloads last month
116
Safetensors
Model size
36.3M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for mussacharles60/swahili-tts-female-voice

Base model

facebook/mms-tts
Finetuned
(4)
this model

Datasets used to train mussacharles60/swahili-tts-female-voice

Space using mussacharles60/swahili-tts-female-voice 1