WaveNet
WaveNet is a deep generative model for raw audio waveforms developed by DeepMind, known for producing highly realistic speech and audio synthesis through neural network architectures.
Neural networks
James L. McClelland
James L. McClelland is a prominent figure in cognitive psychology and artificial intelligence, known for his contributions to connectionist models of cognitive processes.
Neural occupancy field
A neural occupancy field is a representation used in computer vision and graphics to encode 3D shapes or scenes by learning a continuous function that predicts the occupancy status of any point in space. This technique leverages neural networks to model detailed geometric information efficiently.
Arbitrary style transfer
Arbitrary style transfer is a technique in computer vision and neural networks that allows for the application of artistic styles to images.
Random network distillation (RND)
Random network distillation (RND) is a method in reinforcement learning that enhances exploration by utilizing a neural network’s output as a reward signal.
AudioLM (audio language model)
AudioLM is a neural network-based audio language model designed to generate coherent and high-quality audio sequences by learning from raw audio data. It leverages techniques from natural language processing and audio signal processing to produce extended audio continuations without explicit semantic conditioning.
Mixture of experts (MoE)
Mixture of experts (MoE) is a machine learning technique that combines multiple specialized models, or experts, to solve complex tasks by dynamically selecting which expert to use for each input. This approach aims to improve performance and efficiency by leveraging the strengths of individual models within a larger system.
Speaker adaptation for TTS
Speaker adaptation for text-to-speech (TTS) refers to techniques used to modify a TTS system to generate speech in a specific speaker’s voice or style, often using limited data from the target speaker. This process enables more personalized and natural-sounding synthetic speech.
Batch normalization
Batch normalization is a technique used in deep learning to improve the training speed and stability of artificial neural networks by normalizing layer inputs. It helps reduce internal covariate shift, allowing higher learning rates and reducing the sensitivity to initialization.
Generative adversarial network (GAN)
Generative Adversarial Networks (GANs) are a class of machine learning frameworks designed to generate new data instances that resemble a given training dataset.