样本演示

运动估计

ObEN研究团队正在开发人工智能工具,这些工具可以从任何视频中识别、捕捉和模仿人体运动并自动将这些动作用在PAI当中。

脸部追踪

基于你的PAI形象,将脸部动作变为现实——ObEN团队正在研究更好更准确的(使用智能手机或网络摄像头的)脸部追踪技术。

Nikhil的PAI (ObEN CEO)

ObEN的PAI技术能创建跟你长得像说话像的虚拟化身。它能说包括中文日语韩语和英文在内的多种语言。

Adam的PAI (ObEN COO)

世界各地的人都能使用ObEN的PAI——现在由我们联合创始人和COO来演示我们为母语为中文普通话的人创建的PAI。

曾艾佳的PAI(SNH48人气女团成员)

ObEN合作的首个明星PAI在2019年上海世界人工智能大会上首次亮相。

Lucas的PAI (“Discover”频道主持人)

ObEN的PAI技术为Lucas Cochran创建了一个逼真的虚拟化身。Lucas是探索频道每日星球栏目(Discovery Channel’s Daily Planet)的科技特派员。

郑志刚的PAI (K11总裁)

全球首个零售业PAI虚拟礼宾,为了K11上海艺术购物中心所创,是K11创始人兼总裁郑志刚(Adrian Cheng)的虚拟化身——AI将零售体验个性化。

PAI舞

ObEN的PAI能执行各种动作,一切都靠我们的AI技术来生成。只有你想不到的,没有PAI做不到的。

虚拟歌手

只需一段简短的声音样本,我们就可以将任何说话声音转换成音准完美无缺的歌声。你能听出哪个声音是真人哪个是AI吗?

曾艾佳原声
TTS声
PAI唱歌
PAI和人类合唱

具有表达力的TTS

面对TTS技术的重大挑战,我们正在创造可以用多种情感“说话”的数字声音,并让他们更加人性化,更能将我们与我们的听觉体验联系起来。

原声
TTS声
TTS:开心
TTS:生气
TTS:难过

最近发表的论文

ESTHER : Extremely Simple Image Translation Through Self-Regularization

Image translation between two domains is a class of problems where the goal is to learn the mapping from an input image in the source domain to an output image in the target domain. It has important applications such as data augmentation, domain adaptation, and unsupervised training. When paired training data are not accessible, the mapping...

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The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods

We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different state-of-the-art voice conversion (VC) systems. The objective of the challenge was to perform speaker conversion (i.e.\ transform the vocal identity) of a source speaker to...

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A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment

Voice conversion (VC) aims at conversion of speaker characteristic without altering content. Due to training data limitations and modeling imperfections, it is difficult to achieve believable speaker mimicry without introducing processing artifacts; performance assessment of VC, therefore, usually involves both speaker similarity and quality...

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Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention

Image translation between two domains is a class of problems aiming to learn mapping from an input image in the source domain to an output image in the target domain. It has been applied to numerous domains, such as data augmentation, domain adaptation and unsupervised training. When paired training data is not accessible, image translation...

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Investigation of using disentangled and interpretable representations for one-shot cross-lingual voice conversion

This blog post presents a one-shot voice conversion technique, in which a variational autoencoder (VAE) is used to disentangle speech factors. We show that VAEs are able to disentangle the speaker identity and linguistic content from speech acoustic features. Modification of these factors allow transformation of voice. We show that the...

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One-shot Voice Conversion using Variational Autoencoders

This blog post presents a one-shot voice conversion technique, in which a variational autoencoder (VAE) is used to disentangle speech factors. We show that VAEs are able to disentangle the speaker identity and linguistic content from speech acoustic features. Modification of these factors allow transformation of voice. We show that the...

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Voice Approximation for Inter-Gender Voice Personalization

One of the key technologies at ObEN is the personalization of voice identity, consisting of a transformation of an input voice (e.g., from a Text-To-Speech system) to render it perceptually similar to a target one (e.g., a celebrity, or a user’s voice). Although some existing technologies, known as Voice Conversion and based on a statistical...

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ObEN的专利人工智能技术能够迅速将一个人的平面图像和声音结合起来,创造3D虚拟形象。将你的个人3D虚拟形象复制到任何虚拟现实或者增强现实的情境中,享受更深刻,记忆更持久的社交体验。创始于2014年,ObEN是HTC旗下VIVE X速创项目计划中的公司之一,目前在加州帕萨迪纳的领先科技孵化器创意工作室内办公。


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