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OpenAI Whisper Hackathon

The Future of Speech Recognition

Join us for a hackathon where we will be using OpenAI Whisper to create innovative solutions! Whisper is a neural net that has been trained to approach human level robustness and accuracy for English speech recognition. We will be using this tool to create applications that can transcribe in multiple languages, as well as translate from those languages into English. This will be a great opportunity for you to learn more about speech processing and to create some useful applications!
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Hackathon summary video

OpenAI Whisper

Machine learning and artificial intelligence still face challenges when it comes to speech recognition. With OpenAI Whisper, we are one step closer to resolving this problem.

Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web.

This makes it possible to approach human level robustness and accuracy in English speech recognition. It is robust to accents, background noise, and technical language.

It also enables transcription in multiple languages, as well as translation from those languages into English. The Whisper architecture is a simple end-to-end approach, implemented as an encoder-decoder Transformer.

The Challenge

The challenge for this hackathon is to create an innovative solution with OpenAI Whisper.

Plus points if you incorporate other bonus technologies like GPT-3 and Codex . With Whisper's high accuracy and ease of use, we want to see what applications you can create using voice interfaces

Whisper Hackathon details

🗓️ Where and when

The hackathon starts on October 14th and ends on October 16th. Over the weekend, you'll have the opportunity to learn from lablab experts during workshops, keynotes, and mentoring sessions. The hackathon will take place on the lablab.ai platform.

🦸🏼‍♂️ Who should participate?

Previous experience in AI is not required but welcomed. While many participants are industry experts, we also welcome people with other types of domain knowledge that want to understand & explore how AI can be used in their fields.

🛠️ How to participate in the hackathon

The hackathon will take place online on lablab.ai platform and lablab.ai Discord Server. Please register for both in order to participate. To participate click the "Enroll" button at the bottom of the page and read our Hackathon Guidelines.

🔗 Useful links for the hackathon

For general Hackathon information see our Hackathon Guidelines. To learn more about Whisper, see the Whisper documentation. To learn more about GPT-3, see the GPT-3 documentation. To learn more about Codex, see the Codex documentation.

Speakers, Mentors and Organizers

  • Mathias Asberg
    Mentor

    Mathias Asberg

    Founder New Native

  • Paweł Czech
    Speaker

    Paweł Czech

    Founder New Native

  • Alexander Molak
    Speaker

    Alexander Molak

    ML Researcher (R&D) at IRONSCALES

  • Rudradeb Mitra
    Speaker

    Rudradeb Mitra

    Founder Omdena

  • Anastasiia Strakhova
    Organizer

    Anastasiia Strakhova

    Community Manager at New Native

  • Olesia Zinchenko
    Organizer

    Olesia Zinchenko

    Social Media Manager at New Native

Hackathon FAQ

Who can join the Hackathon?

We welcome domain experts from all industries, not just AI or tech. Successful AI solutions require a combination of technical expertise and domain knowledge. Coding experience is recommended.

Do I need a team?

You are welcome to join as a team or solo. If solo, we still encourage you to look for a team before the event, but ultimately it is your choice. We recommend you to join the Deep Learning Labs Discord channel: https://discord.gg/gCuBwBB35k and posting in the #looking-for-team channel to get to know your potential future team members.

Do I need a Github account?

It is recommended. At least one team member should have a Github account. You can create one for free if you don't already have one.

I have other questions.

Feel free to reach us on social media, or through our Discord channel.

Event Schedule

  • To be announced

Winner Submissions 🏆

Submitted concepts, prototypes and pitches

Submissions from the teams participating in the OpenAI Whisper Hackathon event and making it to the end 👊

Phoenix Whisper

Phoenix Whisper

According to research made by J. Birulés-Muntané1 and S. Soto-Faraco (10.1371/journal.pone.0158409), watching movies with subtitles can help us learn a new language more effectively. However, the traditional way of showing subtitles in YouTube or Netflix does not provide us the best way to check the meaning of new vocabulary nor understand complex slang and abbreviation. Therefore, we found out that if we display dual subtitles (the original subtitle of the video and the translated one), the learning curve immediately improves. In research conducted in Japan, the authors concluded that the participants who viewed the episode with dual subtitles did significantly better (http://callej.org/journal/22-3/Dizon-Thanyawatpokin2021.pdf). After understanding both the problem and the solution, we decided to create a platform for learning new languages with dual active transcripts. When you enter a YouTube URL or upload an MP4 file in our web application, the app will produce a web page where you can view the video and have a transcript running next to it in two different languages. We have accomplished this goal and successfully integrated OpenAI Whisper, GPT and Facebook's language model for the backend of the app. At first, we use Streamlit for the app, but it does not provide a transcript that automatically move with the audio timeline, also Streamlit does not give us the ability to design the user interface, so we create our own full stack application using Bootstrap, Flask, HTML, CSS and Javascript. Our business model is subscription-based and/or one-time purchase based on the usage. Our app isn’t just for language learners. It can also be used for writers, singers, YouTubers, or anyone who would like to make their content reach out to more people by adding different languages to their videos/audios. Due to the limitation of free hosting plan, we could not deploy the app on cloud for now but we have a simple website that you can have a quick look at what we are creating (https://phoenixwhisper.onrender.com/success/BzKtI9OfEpk/en).

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