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Found 11 papers, 3 papers with code
4K-Resolution Photo Exposure Correction at 125 FPS with ~8K Parameters
The illumination of improperly exposed photographs has been widely corrected using deep convolutional neural networks or Transformers.
Spike-Triggered Contextual Biasing for End-to-End Mandarin Speech Recognition
However, unlike shallow fusion methods that directly bias the posterior of the ASR model, deep biasing methods implicitly integrate contextual information, making it challenging to control the degree of bias.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Lightweight Improved Residual Network for Efficient Inverse Tone Mapping
But the majority of media images on the internet remain in 8-bit standard dynamic range (SDR) format.
A First Order Meta Stackelberg Method for Robust Federated Learning
Previous research has shown that federated learning (FL) systems are exposed to an array of security risks.
Emotional Talking Head Generation based on Memory-Sharing and Attention-Augmented Networks
Given an audio clip and a reference face image, the goal of the talking head generation is to generate a high-fidelity talking head video.
MAVD: The First Open Large-Scale Mandarin Audio-Visual Dataset with Depth Information
Audio-visual speech recognition (AVSR) gains increasing attention from researchers as an important part of human-computer interaction.
Adaptive Contextual Biasing for Transducer Based Streaming Speech Recognition
By incorporating additional contextual information, deep biasing methods have emerged as a promising solution for speech recognition of personalized words.
Contextualized End-to-End Speech Recognition with Contextual Phrase Prediction Network
In this study, we introduce a contextual phrase prediction network for an attention-based deep bias method.
Online Learning for Adaptive Probing and Scheduling in Dense WLANs
The problem is challenging even when the link rate distributions are pre-known (the offline setting) due to the necessity of balancing the information gains from probing and the cost of reducing the data transmission opportunity.
Joint AP Probing and Scheduling: A Contextual Bandit Approach
In contrast to traditional link scheduling problems under uncertainty, we assume that in each time step, the device can probe a subset of links before deciding which one to use.
Attention-based Residual Speech Portrait Model for Speech to Face Generation
Given a speaker's speech, it is interesting to see if it is possible to generate this speaker's face.
