Search Results for author:
Found 12 papers, 2 papers with code
Speech waveform synthesis from MFCC sequences with generative adversarial networks
This paper proposes a method for generating speech from filterbank mel frequency cepstral coefficients (MFCC), which are widely used in speech applications, such as ASR, but are generally considered unusable for speech synthesis.
A comparison of recent waveform generation and acoustic modeling methods for neural-network-based speech synthesis
Recent advances in speech synthesis suggest that limitations such as the lossy nature of the amplitude spectrum with minimum phase approximation and the over-smoothing effect in acoustic modeling can be overcome by using advanced machine learning approaches.
Speaker-independent raw waveform model for glottal excitation
Recent speech technology research has seen a growing interest in using WaveNets as statistical vocoders, i. e., generating speech waveforms from acoustic features.
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention
Moreover, we experiment with a WaveNet vocoder in synthesis of Lombard speech.
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks
The state-of-the-art in text-to-speech synthesis has recently improved considerably due to novel neural waveform generation methods, such as WaveNet.
Generative adversarial network-based glottal waveform model for statistical parametric speech synthesis
The results show that the newly proposed GANs achieve synthesis quality comparable to that of widely-used DNNs, without using an additive noise component.
GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram
Recent advances in neural network -based text-to-speech have reached human level naturalness in synthetic speech.
Transferring neural speech waveform synthesizers to musical instrument sounds generation
Recent neural waveform synthesizers such as WaveNet, WaveGlow, and the neural-source-filter (NSF) model have shown good performance in speech synthesis despite their different methods of waveform generation.
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech
Spoofing attacks within a logical access (LA) scenario are generated with the latest speech synthesis and voice conversion technologies, including state-of-the-art neural acoustic and waveform model techniques.
Adversarial Guitar Amplifier Modelling With Unpaired Data
We propose an audio effects processing framework that learns to emulate a target electric guitar tone from a recording.
Speaker-independent neural formant synthesis
We also find that the small set of phonetically relevant speech parameters we use is sufficient to allow for speaker-independent synthesis (a. k. a.
Collaborative Watermarking for Adversarial Speech Synthesis
Advances in neural speech synthesis have brought us technology that is not only close to human naturalness, but is also capable of instant voice cloning with little data, and is highly accessible with pre-trained models available.
