The modern digital era has brought forth an abundance of information and content across various media formats, including audio and text. With this surge in content, there arises a need for tools that can assist in deconstructing, analyzing, and reconstructing this media to make it more accessible, understandable, and customizable for different audiences. The problem we aim to address with Decon is the challenge faced by users in managing and interacting with media content efficiently.
Specific challenges include:
- Difficulty in isolating specific elements of audio tracks, such as vocals or instruments, which can be essential for music producers, educators, or enthusiasts wanting to create karaoke tracks, remixes or to simply focus on a particular aspect of the music.
- The barrier language presents in understanding and enjoying content fully. This includes not just translating lyrics or dialogue but also transcribing audio into text for further analysis or accessibility purposes.
- Enhancing textual content through correction, translation, transliteration, explanation, summarization, or even generating new content based on existing patterns.
- The need for a unified platform that integrates various AI tools to address these challenges seamlessly without requiring users to navigate multiple applications or services.
To tackle the aforementioned challenges effectively, we propose the development of Decon - a multimedia workbook application designed as a one-stop solution integrating various AI-powered tools tailored specifically for audio and textual content manipulation.
- Stem Separation: Utilizing Spleeter’s capabilities to split audio files into individual stems (vocals, drums, bass etc.), enabling users to isolate specific elements of a track.
- Voice to Text: Incorporating Whisper ASR technology for accurate speech recognition and transcription services. This feature allows users to convert spoken words into written text efficiently.
- Pitch Adjustment: Offering functionality to adjust the pitch of audio files without significantly affecting their tempo or quality. This could be particularly useful for music practice or analysis.
- Correction & Translation: Implementing advanced NLP models like GPT-4 for real-time correction of grammatical errors and translating text between multiple languages accurately.
- Transliteration & Explanation: Facilitating easy conversion from one script to another while maintaining phonetic accuracy (transliteration) and providing explanations for complex terms or phrases when needed.
- Summarization & Content Generation: Employing AI models capable of summarizing long pieces of text into concise versions without losing essential information and predicting next lines or generating new content based on prompts provided by the user.
-
Frontend Development: Leveraging Vue3 framework’s capabilities for building a user-friendly interface that is responsive and intuitive across devices.
-
Backend Services: Python will serve as the core programming language due to its extensive support for data manipulation and integration with AI models like Spleeter for stem separation and Whisper ASR for speech recognition.
Decon aims to cater to a wide range of users including but not limited to:
- Music enthusiasts looking to create remixes or karaoke versions by isolating vocals/instruments from tracks.
- Language learners wanting translations/transcriptions of songs or dialogues in foreign languages.
- Content creators seeking tools for summarizing meetings/discussions quickly or generating lyrical ideas based on given prompts.
decon@github
{{ gettext('Login to leave a comment') }}
{{ gettext('Post a comment…') }}{{ errorMsg }}
{{ gettext('No comments posted yet') }}