mlsanityData to 14 Oct 2026

Pre-Avatar: An Automatic Presentation Generation Framework Leveraging Talking Avatar

arXiv 2210.06877 ↗First posted 13 Oct 2022cs.AIcited by 6

Not on the map. Why?

Abstract (arXiv)

Since the beginning of the COVID-19 pandemic, remote conferencing and school-teaching have become important tools. The previous applications aim to save the commuting cost with real-time interactions. However, our application is going to lower the production and reproduction costs when preparing the communication materials. This paper proposes a system called Pre-Avatar, generating a presentation video with a talking face of a target speaker with 1 front-face photo and a 3-minute voice recording. Technically, the system consists of three main modules, user experience interface (UEI), talking face module and few-shot text-to-speech (TTS) module. The system firstly clones the target speaker's voice, and then generates the speech, and finally generate an avatar with appropriate lip and head movements. Under any scenario, users only need to replace slides with different notes to generate another new video. The demo has been released here and will be published as free software for use.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 13 Oct 2022.

Builds on

17 of 27 references.

References · 17

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2017VoxCeleb: a large-scale speaker identification datasetcited by 732
  3. 2020A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wildcited by 672
  4. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 561
  5. 2018Deep Audio-Visual Speech Recognitioncited by 322
  6. 2018Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesiscited by 282
  7. 2018Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesiscited by 259
  8. 2018Talking Face Generation by Adversarially Disentangled Audio-Visual Representationcited by 212
  9. 2019MOSNet: Deep Learning based Objective Assessment for Voice Conversioncited by 127
  10. 2020HiFi-GAN: High-Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networkscited by 40
  11. 2022AVQVC: One-shot Voice Conversion by Vector Quantization with applying contrastive learningcited by 24
  12. 2022nnSpeech: Speaker-Guided Conditional Variational Autoencoder for Zero-shot Multi-speaker Text-to-Speechcited by 10
5 more
  1. 2022DRVC: A Framework of Any-to-Any Voice Conversion with Self-Supervised Learningcited by 9
  2. 2022r-G2P: Evaluating and Enhancing Robustness of Grapheme to Phoneme Conversion by Controlled noise introducing and Contextual information incorporationcited by 7
  3. 2022TDASS: Target Domain Adaptation Speech Synthesis Framework for Multi-speaker Low-Resource TTScited by 5
  4. 2022MetaSID: Singer Identification with Domain Adaptation for Metaversecited by 3
  5. 2022Singer Identification for Metaverse with Timbral and Middle-Level Perceptual Featurescited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 3.

6 papers.

  1. 2024EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Modelcited by 12
  2. 2023CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embeddingcited by 2
  3. 2023An Empirical Study of Attention Networks for Semantic Segmentationcited by 0
  4. 2026StreamWise: Serving Multi-Modal Generation in Real-Time at Scalecited by 0
  5. 2026Talking Slide Avatars: Open-Source Multimodal Communication Approach for Teachingcited by 0
  6. 2026EduPanel: A Three-Agent LLM Judge for Teaching Videos -- Reliability, Complementarity, and Human Trust Calibrationcited by 0