Proceedings ArticleDOI
Natural Text-to-Speech Synthesis by Conditioning Spectrogram Predictions from Transformer Network on WaveGlow Vocoder
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TLDR
This work aims to look at some of the issues and limitations present in the current works of Tacotron-2, and attempts to further improve its performance by modifying its architecture.Abstract:
Text to Speech (TTS) is a form of speech synthesis where the text is converted into a spoken human-like voice output. The state of the art methods for TTS employs a neural network based approach. This work aims to look at some of the issues and limitations present in the current works, specifically Tacotron-2, and attempts to further improve its performance by modifying its architecture. The modified model uses Transformer network as a Spectrogram Prediction Network (SPN) and WaveGlow as an Audio Generation Network (AGN). For the modified model, performance improvements are seen in terms of the speech output generated for corresponding texts, the inference time taken for audio generation, and a Mean Opinion Score (MOS) of 4.10 (out of 5) is obtained.read more
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Proceedings ArticleDOI
Spoofing-Aware Speaker Verification with Unsupervised Domain Adaptation
TL;DR: This paper begins the concern of enhancing the spoofing robustness of the automatic speaker verification (ASV) system, without the primary presence of a separate countermeasure module by employing three unsupervised domain adaptation techniques to optimize the back-end using the audio data in the training partition of the ASVspoof 2019 dataset.
Proceedings ArticleDOI
Bi-Sep: A Multi-Resolution Cross-Domain Monaural Speech Separation Framework
TL;DR: In this article , a Bi-Projection Fusion (BPF) mechanism was proposed to merge the information between two domains to improve the fine-grained vision of time-domain methods.
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