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Twi_Akuapem Male TTS Model Vits Encoding Trained on Openbible Dataset at 22050Hz

Twi Akuapem (Twi Akuapem) male text-to-speech model trained at 22050 Hz and is available to synthesize the Twi Akuapem language.

Twi Akuapem (Twi Akuapem) male text-to-speech model trained at 22050 Hz and is available to synthesize the Twi Akuapem language.

Model Description

This Twi Akuapem (Twi Akuapem) male text-to-speech model is trained on the openbible dataset at 22050 Hz and is available to synthesize the Twi Akuapem language. The model is based on the VITS encoder.

pip install tts
tts --text "Hello, world!" --model_name tts_models/tw_akuapem/openbible/vits

Voice Samples

default (M)

Twi Akuapem

Twi Akuapem is a dialect of the Twi language spoken by the Akuapem people of Ghana. It belongs to the Kwa branch of the Niger-Congo language family. Twi Akuapem is primarily spoken in the Akuapem Hills region of Ghana. It has a phonetic system with distinctive vowel sounds and is written using the Latin alphabet. Twi Akuapem plays a significant role in the cultural and social identity of the Akuapem people.

OpenBible Dataset

The OpenBible dataset is a speech dataset that includes recordings of Bible passages read by various speakers. It is commonly used for developing applications related to biblical text processing or speech analysis.

VITS (VQ-VAE-Transformer)

VITS, also known as VQ-VAE-Transformer, is an advanced technique used for training audio models. It combines different components to create powerful models that can understand and generate human-like speech. VITS works by breaking down audio into tiny pieces called vectors, which are like puzzle pieces that represent different parts of the sound. These vectors are then put together using a special algorithm that helps the model learn patterns and understand the structure of the audio. It’s similar to how we put together jigsaw puzzles to form a complete picture. With VITS, the model can not only recognize and understand different speech sounds but also generate new sounds that sound very similar to human speech. This technology has a wide range of applications, from creating realistic voice assistants to helping people with speech impairments communicate more effectively.

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