NLP

How to Use Alibaba’s Wan-S2V Model for Video Creation

Discover Alibaba ’s Wan-S2V, a speech-to-video AI model that turns images and audio into realistic videos. Simple guide for beginners.

By Ananya Rajeev 12 min read
wan s2v model alibaba speech to voice

Introduction

Wan-S2V by Alibaba is a groundbreaking speech-to-video AI model that transforms a single image and an audio clip into a lifelike video. With just a photo and a voice recording, this model can bring characters to life, syncing expressions, lip movements, and gestures with the sound. For beginners, it opens the door to creating engaging videos without technical barriers.

What is Wan-S2V?

Wan-S2V stands for “Wan Speech-to-Video.” It’s a first-of-its-kind open-source AI model from Alibaba that generates videos driven by audio. The model takes an input image and an audio clip. For example, the image might be a photo of a person or character, and the audio could be a recording of someone speaking or singing. From these, it creates a coherent video where the person in the image comes to life and performs in time with the audio. Facial expressions, lip movements, and even body gestures match the speech or music. The result doesn’t feel like a simple lip-synced animation. Instead, it looks much more like a genuine video clip of the person acting out the given audio content.

Alibaba’s Tongyi Lab developed this model as part of their Wan 2.2 series of AI models. This series also includes text-to-video and image-to-video models, and Wan-S2V adds the ability to use audio as a driving input. In other words, most models only use text or images as inputs when generating video. Wan-S2V goes a step further by using sound to guide the video generation. That change makes the generated videos far more engaging and realistic. This is especially evident in scenarios like dialogues, speeches, or music performances.

How Does Wan-S2V Work?

Wan-S2V combines three inputs to create a video:

  • An Image: This is the reference frame for the video, often showing the character or person you want to animate. For example, you could use a portrait photo or an avatar image.
  • An Audio Clip: This is the speech or song that the character should appear to be saying or singing. It provides the voice, timing, and emotion for the video.
  • A Text Prompt (optional): You can also provide a brief text description of the scene or context. For instance, “a man walks along a railway track while singing sadly as a train passes by” could be your prompt. This description sets the scene by describing the background, the mood, or the actions.

Using these inputs, the Wan-S2V model generates a video where:

  • The character’s mouth movements align perfectly with the audio (so the lip-sync is accurate).
  • Facial expressions and body movements reflect the tone and energy of the audio. For example, if the audio is a joyful song, the model might make the character smile, sway, or even dance. If it’s a serious speech, the character might display calm or intense expressions and gestures.
  • The camera perspective and scene follow the text prompt (if provided). In the earlier example prompt, Wan-S2V would try to show the man walking by train tracks with a matching camera angle and environment.

What makes Wan-S2V particularly powerful is how it separates the roles of text and audio. The text prompt handles the big-picture elements: the setting, the camera angles, the scene layout, and overall context. Meanwhile, the audio handles the fine details: the timing, lip movements, and small gestures like head nods or hand movements in rhythm with the sound. By letting text control the scene and audio control the timing, Wan-S2V achieves a natural blend. The model knows what should happen from the text and when it should happen based on the audio. This two-pronged control is why the resulting video feels much more like a real performance than a simple animation.

Under the hood, Wan-S2V is built on a large-scale video diffusion model (nicknamed WAN-14B, indicating a model with 14 billion parameters). This deep learning model learned from many example videos paired with their corresponding audio tracks and images. During training, it learned how movements in video correlate with sounds. For example, the model saw how speaking shapes a person’s mouth movements or how music can influence body language.

It also learned that descriptive text prompts can guide a scene. A separate AI module processes the audio input to extract features like rhythm and intonation. This step ensures the generated video’s motions stay in sync with the audio’s beat and emotion. The result is that Wan-S2V can generate videos where the subject not only lip-syncs convincingly. It also behaves and moves in ways that match both the sound and the described scene.

Key Features and Capabilities

Wan-S2V brings several notable features that set it apart from earlier video generation tools:

  • Full-Body Animation: Wan-S2V can animate more than just a talking face. Depending on how you frame the input image or prompt, it can show half-body or full-body shots. This means the model can handle body gestures and movements, not just facial expressions. For example, if your image is a full-body photo, the output video might show the person walking, turning, or dancing as they speak or sing. This adds a new level of realism.
  • Realistic Facial Expressions and Lip-Sync: The model pays special attention to the face. It ensures that lip movements match the spoken words in the audio precisely, and the facial expressions follow the emotion of the voice. If the audio is angry, expect frowns or intense looks; if it’s happy, expect smiles or an upbeat expression. This emphasis on syncing audio and visuals makes the characters look like they’re truly speaking or singing.
  • Cinematic Camera Work: Uniquely, Wan-S2V can also simulate camera motion and shot composition. Thanks to guidance from the text prompt, the output isn’t limited to a static viewpoint. The model can produce effects like the camera panning, zooming, or changing angles to suit the scene. This gives a cinematic feel to the AI-generated video, as if it were directed by a film director rather than just being a fixed frame.
  • Scene and Environment Control: By using text prompts, you can influence the background setting or the mood of the video. Wan-S2V can interpret prompts that include certain environmental details. For example, adding a phrase like “on a windy night” might make the scene include subtle motions such as blowing hair or swaying trees. The model then adjusts the character’s performance accordingly. It essentially understands some high-level instructions about what’s happening around the character.
  • Longer, Consistent Videos: Many older video generation models struggled to maintain quality or consistency beyond a few seconds. Wan-S2V can handle longer sequences because it remembers what happened earlier in a clip. It keeps the character’s identity and clothing consistent and maintains continuity in movement through the video. You could generate a multi-scene sequence, and the model will try to keep the same character and style throughout. This is very useful for storytelling.
  • Open-Source and Accessible: Alibaba has released Wan-S2V as an open-source project. This means researchers, developers, and creators around the world can access the model freely and even run it themselves (given sufficient hardware). There’s also an online demo available (for instance, on Hugging Face’s website). You can upload your own image and audio to test the model without installing anything. The open nature of Wan-S2V lowers the barrier for creative people everywhere to experiment with AI-driven video generation, without the need for expensive proprietary tools.

Why is Wan-S2V a Big Deal?

Wan-S2V represents a significant step forward in AI video generation for a few reasons. First, it goes beyond the “talking head” paradigm. Previous speech-driven animation tools typically would just animate a face talking, often looking uncanny or limited to a head-and-shoulders frame. In contrast, Wan-S2V delivers a performance – the output video can show the subject acting in a setting, not just speaking into a camera. The difference is like seeing a static newsreader versus watching an actor in a movie scene.

Second, Wan-S2V manages to keep the video quality and synchronization high. According to tests by its developers, this model achieves better realism and clarity than earlier systems. In plain terms, the videos look sharper and the AI does a better job at keeping the character’s appearance consistent. It also excels at maintaining lip-sync accuracy, so the words truly look like they’re coming from the character’s mouth at the right time. This level of quality matters if such AI-generated videos are to be used in professional or creative projects.

Another big deal is that Wan-S2V is free and open-source. Until now, someone who wanted to create this kind of audio-synced video might have had to rely on proprietary services. Some of those services were not even publicly accessible, or they were very costly. Alibaba releasing Wan-S2V openly means a wide community of users can use and improve this technology. Open-source models encourage rapid innovation. Developers can build new applications on top of Wan-S2V. Artists can experiment with it in their creative workflows. Researchers can also study and further improve the model. It effectively democratizes advanced video creation, similar to how open-source image generators (like Stable Diffusion) made artistic image creation accessible to the masses.

Lastly, Wan-S2V shows the potential of multi-modal AI. It’s a model that understands vision (from the image), language (from the text prompt), and audio (from the speech). By blending these, it opens up new creative possibilities. For example, content creators could use it to quickly storyboard a scene for a film by simply describing it. They just provide a character image and some dialogue, and the model does the rest. Educators might create speaking historical figures from a single portrait and a script. The model’s versatility hints at a future where making a short film or an interactive story is far easier. It could become as simple as typing a script, adding a picture, and recording some voice lines.

Potential Applications

Because Wan-S2V can generate convincing videos from minimal inputs, it unlocks a variety of applications:

  • Digital Content Creation: Video creators and filmmakers can use Wan-S2V to pre-visualize scenes or create concept footage. For instance, if a filmmaker has a storyboard image and some recorded dialogue, they could generate a rough video to see how the scene might play out. This can be done before investing in a full shoot.
  • Music Videos: Musicians or fans could create simple music videos by providing a photo and a song. Wan-S2V could animate a character to sing the lyrics and move to the beat. This offers an inexpensive way to produce a lyric video or an animated performance.
  • Virtual Presenters and Educators: You can take a picture of a presenter or historical figure and pair it with an audio narration. With Wan-S2V, this could produce an engaging lecture or storytelling video. Imagine a historical figure’s portrait brought to life to tell their own story in a classroom setting.
  • Marketing and Advertising: Brands might generate promotional videos featuring a mascot or spokesperson speaking a message, without needing a full video shoot. With a brand character image and a voiceover, Wan-S2V can create a talking clip for campaigns or social media.
  • Gaming and Virtual Reality: Game developers or VR creators can quickly prototype cutscenes or character dialogues. By feeding character concept art and dialogue lines, they get a glimpse of how a character might look and move while speaking in the game.
  • Social Media and Entertainment: Individuals could have fun animating selfies or avatars. For example, you could make your own photo sing a popular song or deliver a message in a different voice. This can be entertaining content for social media or personal greetings.

These applications highlight how Wan-S2V lowers the effort to produce customized video content. Anyone with an idea, an image, and some audio can try bringing a visual concept to life. While the technology is still evolving (and it’s not going to replace professional filming quality just yet), it is a powerful creative aid.

How to Try Wan-S2V

Getting started with Wan-S2V is becoming easier thanks to its open-source availability. If you are a developer or technically inclined, you can download the Wan-S2V model from the official repository and run it on a capable computer (bear in mind, generating video requires a strong GPU and plenty of memory). Alibaba’s documentation provides instructions for setting it up, since the model is part of the Wan 2.2 AI toolkit.

For non-technical users or those who just want to experiment, there are also online demos. One such demo is available on the Hugging Face platform, where Wan-S2V is hosted as an interactive web application. In that demo, you can simply upload your chosen image and audio file, input a text prompt if you have one, and then let the model generate a short video for you. This makes it easy to see the model in action without any complex installation.

Keep in mind that results may vary depending on the input quality and the complexity of the request. The model might not get everything perfect – for example, very fast speech or crowded scenes might still be tricky. However, the fact that this technology is at your fingertips is exciting. As hardware and models improve, we can expect even longer and more detailed videos to be generated with similar ease.

wan s2v model alibaba speech to voice
wan-s2v-model-alibaba-speech-to-voice

Conclusion

Wan-S2V is a breakthrough in AI-driven video generation, bringing us closer to a world where creating a realistic video is as straightforward as providing an image and a sound. For beginners and professionals alike, it offers a glimpse into the future of content creation: one where AI can take a simple idea (a picture and a voice) and turn it into a vivid video scene. Alibaba ’s speech-to-video model stands out not just for its technical achievements, but for making this technology accessible globally through open-source release.

In summary, Alibaba ‘s Wan-S2V transforms static images and audio into living scenes. A single photograph can talk, sing, and perform with authentic emotion and presence. The model’s ability to blend visual, auditory, and textual cues means that we can craft stories and share ideas in a more dynamic way than ever before. As AI models like Wan-S2V continue to advance, the line between imagination and reality in video creation will only get thinner. This progress will empower anyone to become a creator of rich, animated content.

Keep Exploring AI Innovations

If you found Alibaba ’s Wan-S2V speech-to-video model fascinating, you’ll enjoy these related posts:

External Resources

Ananya Rajeev

Ananya Rajeev is a Kerala-born data scientist and AI enthusiast who simplifies generative and agentic AI for curious minds. B.Tech grad, code lover, and storyteller at heart.