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German Male TTS Model Tacotron2 DDC Encoding Trained on Thorsten Dataset at 22050Hz

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

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

Model Description

This German (Deutsch) male text-to-speech model is trained on the the Thorsten dataset at 22050 Hz and is available to synthesize the German language. The model is based on the Tacotron 2 encoder.

pip install tts
tts --text "Hello, world!" --model_name tts_models/de/thorsten/tacotron2-DDC

Voice Samples

default (M)

German (Deutsch)

German is a West Germanic language primarily spoken in Germany, Austria, Switzerland, and Liechtenstein. It belongs to the Indo-European language family and is closely related to English, Dutch, and the Scandinavian languages. German has a rich literary tradition and is known for its compound words and grammatical complexity. It uses the Latin alphabet and includes umlauts (ä, ö, ü) and the Eszett (ß) as additional characters. German is classified as a Germanic language within the larger West Germanic branch.

Thorsten Dataset

The Thorsten dataset is a speech dataset that includes recordings from a single speaker. It can be used for training and evaluating speech recognition or synthesis models, as well as other speech-related applications.

Tacotron 2 DDC

Tacotron 2 is an exciting technology used for training audio models, specifically for text-to-speech synthesis. It’s like having a virtual voice that can read text aloud in a natural and human-like manner. Tacotron 2 uses deep learning algorithms to learn the patterns and nuances of human speech from large amounts of training data. It takes text as input and converts it into speech by generating a corresponding sequence of audio signals. The model learns how to pronounce words, intonations, and even subtle details like pauses and inflections, making the synthesized speech sound remarkably natural. Tacotron 2 has various applications, including creating voice-overs for videos, aiding individuals with speech disabilities, and even personalizing virtual assistants to have unique and expressive voices. Tacotron 2 with Double Decoder Consistency (DDC) is an advanced TTS model that addresses attention alignment issues during inference. It uses two decoders with different reduction factors to improve alignment performance. DDC enhances Tacotron 2’s architecture, which includes an encoder, attention module, decoder, and Postnet. By measuring consistency between the decoders, DDC mitigates attention problems caused by out-of-domain words or long input texts. It provides more accurate and natural-sounding speech synthesis.

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