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Found 12 papers, 2 papers with code
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
In addition, we find Vall-E could preserve the speaker's emotion and acoustic environment of the acoustic prompt in synthesis.
Learning to mask: Towards generalized face forgery detection
Our goal is to reduce the features that are easy to learn in the training phase, so as to reduce the risk of overfitting on specific forgery types.
General GAN-generated image detection by data augmentation in fingerprint domain
To our knowledge, we are the first to conduct data augmentation in the fingerprint domain.
Describing emotions with acoustic property prompts for speech emotion recognition
We investigate how the model can learn to associate the audio with the descriptions, resulting in performance improvement of Speech Emotion Recognition and Speech Audio Retrieval.
Real-Time Joint Personalized Speech Enhancement and Acoustic Echo Cancellation with E3Net
We dedicate the early layers to the AEC task while encouraging later layers for personalization by adding a bypass connection from the early layers to the mask prediction layer.
Audio Retrieval with WavText5K and CLAP Training
In this work, we propose a new collection of web audio-text pairs and a new framework for retrieval.
Fast Real-time Personalized Speech Enhancement: End-to-End Enhancement Network (E3Net) and Knowledge Distillation
Our results show that E3Net provides better speech and transcription quality with a lower target speaker over-suppression (TSOS) rate than the baseline model.
One model to enhance them all: array geometry agnostic multi-channel personalized speech enhancement
Experimental results show that the proposed geometry agnostic model outperforms the model trained on a specific microphone array geometry in both speech quality and automatic speech recognition accuracy.
Personalized Speech Enhancement: New Models and Comprehensive Evaluation
Our results show that the proposed models can yield better speech recognition accuracy, speech intelligibility, and perceptual quality than the baseline models, and the multi-task training can alleviate the TSOS issue in addition to improving the speech recognition accuracy.
Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement
Performance analysis is also carried out by changing the ASR model, the data used for the ASR-step, and the schedule of the two update steps.
Advances in Online Audio-Visual Meeting Transcription
This increases marginally to 1. 6% when 50% of the attendees are unknown to the system.
Attention-Aware Compositional Network for Person Re-identification
AACN consists of two main components: Pose-guided Part Attention (PPA) and Attention-aware Feature Composition (AFC).
