VALL-E

VALL-E 2 is the latest advancement in neural codec language models that marks a milestone in zero-shot text-to-speech synthesis (TTS), achieving human parity for the first time. Building upon the foundation laid by its predecessor, VALL-E, the new iteration introduces two significant enhancements to elevate its performance: Repetition Aware Sampling refines the original nucleus sampling process by accounting for token repetition in the decoding history. It not only stabilizes the decoding but also circumvents the infinite loop issue encountered in VALL-E. Grouped Code Modeling organizes codec codes into groups to effectively shorten the sequence length, which not only boosts inference speed but also addresses the challenges of long sequence modeling. Our experiments, conducted on the LibriSpeech and VCTK datasets, have shown that VALL-E 2 surpasses previous zero-shot TTS systems in speech robustness, naturalness, and speaker similarity. It is the first of its kind to reach human parity on these benchmarks. Moreover, VALL-E 2 consistently synthesizes high-quality speech, even for sentences that are traditionally challenging due to their complexity or repetitive phrases.

This page is for research demonstration purposes only. Currently, we have no plans to incorporate VALL-E 2 into a product or expand access to the public.

Grouped code modeling not only accelerates inference by reducing the sequence length but also improves performance by mitigating the long context modeling problem. Based on the token repetition in the decoding history, repetition aware sampling enhances the stability of the decoding process and circumvents the infinite loop issue encountered in VALL-E.		VALL-E 2 achieves human parity zero-shot TTS performance for the first time. In this context, human parity indicates that the robustness, naturalness, and similarity metrics of VALL-E 2 surpass those of the ground truth samples ( WER(GroundTruth) − WER(VALL-E 2) >0, CMOS(VALL-E 2) − CMOS(GroundTruth) >0, and SMOS(VALL-E 2) − SMOS(GroundTruth)>0), meaning that VALL-E 2 can generate accurate, natural speech in the exact voice of the original speaker, comparable to human performance. It is important to note that this conclusion is drawn solely from experimental results on the LibriSpeech and VCTK datasets.

Audio Samples

• VALL-E 2 can synthesize personalized speech even with the hard text from ELLA-V. The speaker prompts are sampled from the librispeech dataset.

  Text	Speaker Prompt	VALL-E	VALL-E 2
  F one F two F four F eight H sixteen H thirty two H sixty four
  Clever cats carefully crafted colorful collages creating cheerful compositions
  Curious koalas curiously climbed curious curious climbers
  Sad snakes sadly sighed sad sad sighs
  Joyful jaguars joyfully jumped joyful joyful jumps
  Noisy newts nonsensically nibbled noisy noisy nibbles
  Crafting a symphony of flavors the skilled chef orchestrated a culinary masterpiece that left an indelible mark mark mark mark mark on the palates of the discerning diners
  The future belongs to belongs to belongs to belongs to belongs to those who believe in the beauty of the beauty of the beauty of the beauty of the beauty of their dreams

• VALL-E 2 can perform zero-shot speech continuation with the first 3-second prefix as the speaker prompt, and speech synthesis with a reference utterance of an unseen speaker as the speaker prompt. The audio and transcriptions are sampled from the LibriSpeech dataset.

  Text	Speaker Prompt (Prefix/Ref)	VALL-E	VALL-E 2 (GroupSize=1)	VALL-E 2 (GroupSize=2)	VALL-E 2 (GroupSize=4)
  They moved thereafter cautiously about the hut groping before and about them to find something to show that Warrenton had fulfilled his mission
  And lay me down in thy cold bed and leave my shining lot
  Number ten fresh nelly is waiting on you good night husband
  Yea his honourable worship is within but he hath a godly minister or two with him and likewise a leech
  Instead of shoes the old man wore boots with turnover tops and his blue coat had wide cuffs of gold braid

• Zero-shot TTS from 3-second, 5-second and 10-second speaker prompts. The audio and transcriptions are sampled from the VCTK dataset.

  Text	Speaker Prompt (3s/5s/10s)	VALL-E	VALL-E 2 (GroupSize=1)	VALL-E 2 (GroupSize=2)	VALL-E 2 (GroupSize=4)
  We have to reduce the number of plastic bags
  So what is the campaign about
  My life has changed a lot
  Nothing is yet confirmed
  I could hardly move for the next couple of days