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The MSXF TTS System for ICASSP 2022 ADD Challenge

arXiv 2201.11400 ↗First posted 27 Jan 2022cs.SD cs.AI eess.AScited by 0

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Abstract (arXiv)

This paper presents our MSXF TTS system for Task 3.1 of the Audio Deep Synthesis Detection (ADD) Challenge 2022. We use an end to end text to speech system, and add a constraint loss to the system when training stage. The end to end TTS system is VITS, and the pre-training self-supervised model is wav2vec 2.0. And we also explore the influence of the speech speed and volume in spoofing. The faster speech means the less the silence part in audio, the easier to fool the detector. We also find the smaller the volume, the better spoofing ability, though we normalize volume for submission. Our team is identified as C2, and we got the fourth place in the challenge.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 15 references that are in the map. First posted on arXiv 27 Jan 2022.

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References · 13

  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  2. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,139
  3. 2020FastSpeech 2: Fast and High-Quality End-to-End Text to Speechcited by 710
  4. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 555
  5. 2021WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognitioncited by 189
  6. 2021AdaSpeech: Adaptive Text to Speech for Custom Voicecited by 98
  7. 2021Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representationscited by 81
  8. 2021End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detectioncited by 68
  9. 2021What all do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structurecited by 52
  10. 2021One TTS Alignment To Rule Them Allcited by 47
  11. 2020MultiSpeech: Multi-Speaker Text to Speech with Transformercited by 42
  12. 2020g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Datasetcited by 15
1 more
  1. 2020From Speaker Verification to Multispeaker Speech Synthesis, Deep Transfer with Feedback Constraintcited by 14

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