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English Female TTS Model Tacotron2 DDC_ph Encoding Trained on Ljspeech Dataset at 22050Hz

English female text-to-speech model trained on the ljspeech dataset at 22050 Hz and is available to synthesize the English language.

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English female text-to-speech model trained on the ljspeech dataset at 22050 Hz and is available to synthesize the English language.

Model Description

This English female text-to-speech model is trained on the the LJSpeech dataset at 22050 Hz and is available to synthesize the English language. The model is based on the Tacotron 2 encoder.

pip install tts
tts --text "Hello, world!" --model_name tts_models/en/ljspeech/tacotron2-DDC_ph

Voice Samples

default (F)

English

English is a West Germanic language that originated in England and is now one of the most widely spoken languages in the world. It belongs to the Indo-European language family and is closely related to German and Dutch. English has a diverse vocabulary and is known for its global influence as a lingua franca. It uses the Latin alphabet with modifications, including the addition of letters such as ð and þ in Old English. English features a complex phonetic system with a wide range of vowel and consonant sounds.

LJSpeech Dataset

The LJSpeech dataset is a large-scale English speech dataset that contains single-speaker recordings. It is commonly used for training and evaluating text-to-speech (TTS) models.

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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