{"type": "project", "title": "Type2Vid", "logoImg": "bafkreibb3wagqmxbo4blpatdzx3pz5pjjihoj7ab2hgdyuhdovp5ugqpya", "website": "https://www.type2Vid.ai", "bannerImg": "bafkreicwcg45oefh5bc5mtyxcvxsxxaoacoskhpriurigqdklcpft5r72a", "createdAt": 1703861819698, "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..Z3IOW70PZ9tPrMC3zHlBV6LTSneX_pQC1WejMZW_zbvhccf5vdneS2isOYTLwxuxtbJB3qd-ovqohRRy7150Cw", "type": "Ed25519Signature2018", "created": "2023-12-29T14:49:04.583Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-12-29T14:49:04.583Z", "expirationDate": "2024-03-28T14:49:04.583Z", "credentialSubject": {"id": "did:pkh:eip155:1:0xcD6F0E15cA8AdecbC7c0CEdb7b2997E488888888", "hash": "v0.0.0:nRy5pbBrBG2xR/DdUG5DC347VpHfpffVvoyt4450tRA=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#type2vid"}}}, "description": "Type2Vid.ai The first AI technology platform to empower Web3 projects\n\nThe most advanced AI text-generated video large multimodal model, the user threshold is low and the cost of use is low.\nType2Vid is an aggregation platform that empowers Web 3 projects with AI technology and continuously issues new AI Base projects.\nIn the future, decentralized GPU power AIOS will be developed and $TYPE tokens will be issued to make it accessible to users around the world.\n\nPlease see our presentation that accompanies this proposal:\nhttps://docsend.com/view/k54rixcxuxxk5dfw\n\nType2Vid.ai through the use of neural networks and rendering technology to achieve realistic character video synthesis. The user inputs the text content expected to be spoken by the target speaker, and the text content will be converted into the audio of the target speaker's timbre. The output speech is natural, expressive, and indistinguishable from the target speaker's voice. Then use the audio to edit the head video of the target speaker to generate a high-quality and lip-synced output video that is consistent even under different emotions.\n\n1. Extract the source audio speech feature: \nFirst, perform pre-training to extract the source audio speech feature from the target speaker's voice source file to form an audio corpus, support users to directly input text, directly convert text to speech through the function of TTS, and then the extracted audio speech feature is given to the speech file converted by text.\n\n2. Predict facial shapes and textures: \nSecondly, predict facial shapes and textures from a single image of the target speaker. \n\n3. Lip synchronization is applied to the source video: \nFinally, the face shape that needs to be matched with the speech content predicted by the voice file generated in the first step is applied to the source video to achieve lip synchronization. \n\nType2Vid.ai provides text-generated video to build basic models for global users, and continues to improve and optimize, and will support more languages in the future, including Spanish, Russian, Japanese, Korean..., providing top-level text-generated speech, voice cloning, voice fusion with lip movements and expressions, and other cutting-edge AI technologies.\n\nAdvantages and applications: The lip synchronization algorithm proposed by Type2Vid can not only achieve realistic lip synchronization while maintaining the target speaker's expression, head posture and other features, but also has a wide range of application prospects in video-related industries. Let's take a deeper look:\nWidely used domain: It can be applied to domains such as movies, short videos, advertisements, education, training, virtual reality, conferences, etc. For example:\n- In entertainment such as live broadcasts and short videos, the real person can record the video of any voice content in advance, and only needs to change the text content each time, which can quickly generate new live broadcasts or short video content without the process of shooting and editing.\n- In advertising, the spokesperson can record the video in advance, and the advertiser can enter the text at any time to create a new advertising video based on the spokesperson according to the different needs of different stages, without the spokesperson re-shooting and editing the video advertisement.\n- In the field of education and training, it can be used by real teachers to create interactive learning experiences, improve the learning effect and have fun.\n- In filmmaking, this technology can help make film dubbing more realistic.\n- In virtual reality, technology can enhance the user's immersion and experience.\n- In scenarios such as remote meetings, this technology can make communication between participants more natural and authentic.\n- In translation, technology translates the entire video into different languages or modifies the voice after the video is recorded.\n\nType2Vid.ai will ultimately establish a decentralized GPU computing platform based on the Arbitrum One blockchain. Users participate in Type2Vid text generation video-related computing work according to hardware configuration requirements, realize decentralized data computing architecture. Ultimately, the following goals are achieved:\n- Consistent use of data and information\n- Data deletion after processing\n- Anonymization of sensitive personal or business data", "logoImgData": {}, "bannerImgData": {}, "projectTwitter": "type2vid"}
Type2Vid
Type2Vid.ai The first AI technology platform to empower Web3 projects

The most advanced AI text-generated video large multimodal model, the user threshold is low and the cost of use is low.
Type2Vid is an aggregation platform that empowers Web 3 projects with AI technology and continuously issues new AI Base projects.
In the future, decentralized GPU power AIOS will be developed and $TYPE tokens will be issued to make it accessible to users around the world.

Please see our presentation that accompanies this proposal:
https://docsend.com/view/k54rixcxuxxk5dfw

Type2Vid.ai through the use of neural networks and rendering technology to achieve realistic character video synthesis. The user inputs the text content expected to be spoken by the target speaker, and the text content will be converted into the audio of the target speaker's timbre. The output speech is natural, expressive, and indistinguishable from the target speaker's voice. Then use the audio to edit the head video of the target speaker to generate a high-quality and lip-synced output video that is consistent even under different emotions.

1. Extract the source audio speech feature: 
First, perform pre-training to extract the source audio speech feature from the target speaker's voice source file to form an audio corpus, support users to directly input text, directly convert text to speech through the function of TTS, and then the extracted audio speech feature is given to the speech file converted by text.

2. Predict facial shapes and textures: 
Secondly, predict facial shapes and textures from a single image of the target speaker. 

3. Lip synchronization is applied to the source video: 
Finally, the face shape that needs to be matched with the speech content predicted by the voice file generated in the first step is applied to the source video to achieve lip synchronization. 

Type2Vid.ai provides text-generated video to build basic models for global users, and continues to improve and optimize, and will support more languages in the future, including Spanish, Russian, Japanese, Korean..., providing top-level text-generated speech, voice cloning, voice fusion with lip movements and expressions, and other cutting-edge AI technologies.

Advantages and applications: The lip synchronization algorithm proposed by Type2Vid can not only achieve realistic lip synchronization while maintaining the target speaker's expression, head posture and other features, but also has a wide range of application prospects in video-related industries. Let's take a deeper look:
Widely used domain: It can be applied to domains such as movies, short videos, advertisements, education, training, virtual reality, conferences, etc. For example:
- In entertainment such as live broadcasts and short videos, the real person can record the video of any voice content in advance, and only needs to change the text content each time, which can quickly generate new live broadcasts or short video content without the process of shooting and editing.
- In advertising, the spokesperson can record the video in advance, and the advertiser can enter the text at any time to create a new advertising video based on the spokesperson according to the different needs of different stages, without the spokesperson re-shooting and editing the video advertisement.
- In the field of education and training, it can be used by real teachers to create interactive learning experiences, improve the learning effect and have fun.
- In filmmaking, this technology can help make film dubbing more realistic.
- In virtual reality, technology can enhance the user's immersion and experience.
- In scenarios such as remote meetings, this technology can make communication between participants more natural and authentic.
- In translation, technology translates the entire video into different languages or modifies the voice after the video is recorded.

Type2Vid.ai will ultimately establish a decentralized GPU computing platform based on the Arbitrum One blockchain. Users participate in Type2Vid text generation video-related computing work according to hardware configuration requirements, realize decentralized data computing architecture. Ultimately, the following goals are achieved:
- Consistent use of data and information
- Data deletion after processing
- Anonymization of sensitive personal or business data
Type2Vid