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unite10mon
HierSpeech++ : Hierarchical Variational Inference for Zero-shot Speech Synthesis
The framework also employs a hierarchical adaptive generator(HAG) to generate semantic ... and utilizes a monotonic alignment search coupled with a variational autoencoder to align the speech and text ...
IEEE11mon
Attn-VAE-GAN:Text-Driven High-Fidelity Image Generation Model with Deep Fusion of Self-Attention and Variational Autoencoder
The initial integration of a generator module featuring a fused Self ... capture intricate semantic information from the input text. Moreover, the assimilation of a Variational Autoencoder (VAE) ...
EurekAlert!1y
Deep variational autoencoder for proteomics mass spectrometry data analysis
1a). Next, Dear-DIA uses a variational autoencoder to extract the peak features of fragment ions and maps the features into Euclidean space, and then clusters the features, with different classes ...
eLife1y
Disentangled multi-subject and social behavioral representations through a constrained subspace variational autoencoder (CS-VAE)
This paper is a valuable step in multi-subject behavioral modeling using an extension of the Variational Autoencoder (VAE ... Here we show two example tasks: (1) Motif generation: we apply state space ...
syncedreview1y
Google & CMU’s Semantic Pyramid AutoEncoder Marks the First Successful Attempt for Multimodal Generation with Frozen LLMs
To bridge this gap, in a new paper SPAE: Semantic Pyramid AutoEncoder for Multimodal ... to conduct conditional image understanding and generation tasks without the demand of training on relevant ...
Microsoft2y
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation
Variational Auto-Encoder (VAE) has been widely adopted in text generation. Among many variants, recurrent VAE learns token-wise latent variables with each conditioned on the preceding ones, which ...