50 citations · 51 across the 3 of their papers we have counts for
8 papers
Glottal Source Processing: from Analysis to Applications
Thomas Drugman, Paavo Alku, Abeer Alwan +1
The great majority of current voice technology applications relies on acoustic features characterizing the vocal tract response, such as the widely used MFCC of LPC parameters. Non…
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech
Xin Wang, Junichi Yamagishi, Massimiliano Todisco +37
Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is v…
GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram
Lauri Juvela, Bajibabu Bollepalli, Junichi Yamagishi +1
Recent advances in neural network -based text-to-speech have reached human level naturalness in synthetic speech. The present sequence-to-sequence models can directly map text to m…
Generative adversarial network-based glottal waveform model for statistical parametric speech synthesis
Bajibabu Bollepalli, Lauri Juvela, Paavo Alku
Recent studies have shown that text-to-speech synthesis quality can be improved by using glottal vocoding. This refers to vocoders that parameterize speech into two parts, the glot…
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks
Lauri Juvela, Bajibabu Bollepalli, Junichi Yamagishi +1
The state-of-the-art in text-to-speech synthesis has recently improved considerably due to novel neural waveform generation methods, such as WaveNet. However, these methods suffer…
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention
Bajibabu Bollepalli, Lauri Juvela, Paavo Alku
Currently, there are increasing interests in text-to-speech (TTS) synthesis to use sequence-to-sequence models with attention. These models are end-to-end meaning that they learn b…