mlsanityData to 7 Oct 2026

The AS-NU System for the M2VoC Challenge

arXiv 2104.03009 ↗First posted 7 Apr 2021eess.AS cs.LG cs.SDcited by 1

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Abstract (arXiv)

This paper describes the AS-NU systems for two tracks in MultiSpeaker Multi-Style Voice Cloning Challenge (M2VoC). The first track focuses on using a small number of 100 target utterances for voice cloning, while the second track focuses on using only 5 target utterances for voice cloning. Due to the serious lack of data in the second track, we selected the speaker most similar to the target speaker from the training data of the TTS system, and used the speaker's utterances and the given 5 target utterances to fine-tune our model. The evaluation results show that our systems on the two tracks perform similarly in terms of quality, but there is still a clear gap between the similarity score of the second track and the similarity score of the first track.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 20 references that are in the map. First posted on arXiv 7 Apr 2021.

Builds on

14 of 20 references.

References · 14

  1. 2016WaveNet: A Generative Model for Raw Audiocited by 1,710
  2. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 800
  3. 2018ESPnet: End-to-End Speech Processing Toolkitcited by 554
  4. 2015Attention-Based Models for Speech Recognitioncited by 400
  5. 2019Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogramcited by 337
  6. 2018WaveGlow: A Flow-based Generative Network for Speech Synthesiscited by 308
  7. 2018Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesiscited by 280
  8. 2016SampleRNN: An Unconditional End-to-End Neural Audio Generation Modelcited by 110
  9. 2018Neural Voice Cloning with a Few Samplescited by 100
  10. 2019Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddingscited by 73
  11. 2018Sample Efficient Adaptive Text-to-Speechcited by 45
  12. 2018Fitting New Speakers Based on a Short Untranscribed Samplecited by 18
2 more
  1. 2019High quality, lightweight and adaptable TTS using LPCNetcited by 11
  2. 2021The Multi-speaker Multi-style Voice Cloning Challenge 2021cited by 7

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Citing papers per year: 2021: 1.

1 paper.

  1. 2021A Survey on Neural Speech Synthesiscited by 182