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Found 6 papers, 2 papers with code
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging
In this paper, we experimented with transfer learning and adaptation of a Tacotron2 text-to-speech model to improve the final synthesis quality of ultrasound-based articulatory-to-acoustic mapping with a limited database.
Advances in Speech Vocoding for Text-to-Speech with Continuous Parameters
Vocoders received renewed attention as main components in statistical parametric text-to-speech (TTS) synthesis and speech transformation systems.
Continuous Wavelet Vocoder-based Decomposition of Parametric Speech Waveform Synthesis
To date, various speech technology systems have adopted the vocoder approach, a method for synthesizing speech waveform that shows a major role in the performance of statistical parametric speech synthesis.
Self-Attention Networks for Intent Detection
Self-attention networks (SAN) have shown promising performance in various Natural Language Processing (NLP) scenarios, especially in machine translation.
Transformer based Grapheme-to-Phoneme Conversion
The transformer network architecture is completely based on attention mechanisms, and it outperforms sequence-to-sequence models in neural machine translation without recurrent and convolutional layers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Ultrasound-based Silent Speech Interface Built on a Continuous Vocoder
Recently it was shown that within the Silent Speech Interface (SSI) field, the prediction of F0 is possible from Ultrasound Tongue Images (UTI) as the articulatory input, using Deep Neural Networks for articulatory-to-acoustic mapping.
Sound Audio and Speech Processing
