Blog(2)

• Robust neural codec language modeling with phoneme position prediction for zero-shot TTS

  Large language models (LLMs) have exhibited impressive in-context learning abilities [1]. Inspired by these successes, recent studies [2-5] have extended LLM applications to text-to-speech (TTS) systems by representing speech through discrete acoustic codes.

• [CVPR 2023 Series #7] Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style

  Zero-shot sketch-based image retrieval (ZS-SBIR) is a central problem to sketch understanding [6]. This paper aims to tackle all problems associated with the current status quo for ZS-SBIR, including category-level (standard) [4], fine-grained [1], and cross-dataset [3].

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Publications(21)

• Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP

  AuthorShell Xu Hu

  PublishedConference on Empirical Methods in Natural Language Processing (EMNLP)

  Date2024-11-13

• CLIP-DPO: Vision-Language Models as a Source of Preference for Fixing Hallucinations in LVLMs

  AuthorYassine Ouali, Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos

  PublishedEuropean Conference on Computer Vision (ECCV)

  Date2024-09-30

• Modularized Multilingual NMT with Fine-grained Interlingua

  AuthorSungjun Lim, Yoonjung Choi, Sangha Kim

  PublishedNorth American Chapter of the Association for Computational Linguistics (NAACL)

  Date2024-06-20

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News(6)

• [Blog] Robust neural codec language modeling with phoneme position prediction for zero-shot TTS

  Large language models (LLMs) have exhibited impressive in-context learning abilities [1]. Inspired by these successes, recent studies [2-5] have extended LLM applications to text-to-speech (TTS) systems by representing speech through discrete acoustic codes.

• [Blog] Fairness in Dysarthric Speech Synthesis: Understanding Intrinsic Bias in Dysarthric Speech Cloning using F5-TTS

  Voice cloning, especially zero-shot speech synthesis, has become one of the most exciting frontiers in speech technology.

• [Blog] Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis

  Recently, personalized AI systems have gained significant attention. In the TTS field, zero-shot text-to-speech (ZS-TTS) systems [1-7] enable users to create their own TTS systems that replicate their voices with just one utterance, without further training.

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