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TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian Portuguese

2020-05-11 · Edresson Casanova, Arnaldo Candido Junior, Christopher Shulby, Frederico Santos de Oliveira, João Paulo Teixeira, Moacir Antonelli Ponti, Sandra Maria Aluisio

Speech provides a natural way for human-computer interaction. In particular, speech synthesis systems are popular in different applications, such as personal assistants, GPS applications, screen readers and accessibility tools. However, not all languages are on the same level when in terms of resources and systems for speech synthesis. This work consists of creating publicly available resources for Brazilian Portuguese in the form of a novel dataset along with deep learning models for end-to-end speech synthesis. Such dataset has 10.5 hours from a single speaker, from which a Tacotron 2 model with the RTISI-LA vocoder presented the best performance, achieving a 4.03 MOS value. The obtained results are comparable to related works covering English language and the state-of-the-art in Portuguese.

📄 PDF Abstract BibTeX arXiv:2005.05144

Code (1)

Edresson/TTS-Portuguese-Corpus 공식 구현

Tasks

DenoisingSpeech SynthesisTransfer Learning

Methods 이 논문이 사용한 방법론

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
WaveRNN WaveRNN is a single-layer recurrent neural network for audio generation that is designed efficiently predict 16-bit raw audio samples. The overall computation in the…
Griffin-Lim Algorithm The Griffin-Lim Algorithm (GLA) is a phase reconstruction method based on the redundancy of the short-time Fourier transform. It promotes the consistency of a spectrogram by…
Sigmoid Activation 설명 없음
Highway Layer 설명 없음
Residual Connection 설명 없음
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…
Batch Normalization 설명 없음

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