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Found 11 papers, 2 papers with code
A unified multichannel far-field speech recognition system: combining neural beamforming with attention based end-to-end model
Far-field speech recognition is a challenging task that conventionally uses signal processing beamforming to attack noise and interference problem.
A Method for Identifying Origin of Digital Images Using a Convolution Neural Network
The rapid development of deep learning techniques has created new challenges in identifying the origin of digital images because generative adversarial networks and variational autoencoders can create plausible digital images whose contents are not present in natural scenes.
Security of Facial Forensics Models Against Adversarial Attacks
We experimentally demonstrated the existence of individual adversarial perturbations (IAPs) and universal adversarial perturbations (UAPs) that can lead a well-performed FFM to misbehave.
Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddings
While speaker adaptation for end-to-end speech synthesis using speaker embeddings can produce good speaker similarity for speakers seen during training, there remains a gap for zero-shot adaptation to unseen speakers.
Audio and Speech Processing
Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detection
Advanced neural language models (NLMs) are widely used in sequence generation tasks because they are able to produce fluent and meaningful sentences.
Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
The output of one branch of the decoder is used for segmenting the manipulated regions while that of the other branch is used for reconstructing the input, which helps improve overall performance.
Speaker Anonymization Using X-vector and Neural Waveform Models
One solution to mitigate these concerns involves the concealing of speaker identities before the sharing of speech data.
Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet
We propose using an extended model architecture of Tacotron, that is a multi-source sequence-to-sequence model with a dual attention mechanism as the shared model for both the TTS and VC tasks.
Audiovisual speaker conversion: jointly and simultaneously transforming facial expression and acoustic characteristics
Transforming the facial and acoustic features together makes it possible for the converted voice and facial expressions to be highly correlated and for the generated target speaker to appear and sound natural.
High-quality nonparallel voice conversion based on cycle-consistent adversarial network
Although voice conversion (VC) algorithms have achieved remarkable success along with the development of machine learning, superior performance is still difficult to achieve when using nonparallel data.
Generative Adversarial Network
Image-to-Image Translation
+4
Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data
Thanks to the growing availability of spoofing databases and rapid advances in using them, systems for detecting voice spoofing attacks are becoming more and more capable, and error rates close to zero are being reached for the ASVspoof2015 database.
