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Polish Male TTS Model Vits Encoding Trained on Mai_female Dataset at 22050Hz

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

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

Model Description

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

pip install tts
tts --text "Hello, world!" --model_name tts_models/pl/mai_female/vits

Voice Samples

default (M)

Polish (polski)

Polish is a West Slavic language spoken primarily in Poland. It belongs to the Indo-European language family and is closely related to Czech and Slovak. Polish has a complex grammar with noun declensions, verb conjugations, and grammatical gender. It uses the Latin alphabet with diacritic marks to represent specific sounds. Polish has a phonetic property called nasal vowels, where the air passes through the nose during vowel pronunciation.

MAI Female Dataset

The MAI Female dataset is a subset of the MAI dataset that includes speech recordings from female speakers. It can be used for specific research or applications that require female voice data.

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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