QA-MDT is an open-source music generation model that integrates state-of-the-art models for music creation. It is based on various open-source projects, including AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. The QA-MDT model can generate high-quality music by utilizing diverse training strategies. It is particularly suitable for researchers and developers interested in music generation.

pdf-to-podcast is an AI-powered productivity tool that transforms PDF documents into podcast episodes. It utilizes OpenAI's text-to-speech model and Google Gemini technology to process PDF content into natural dialogue suitable for audio podcasts, outputting as MP3 files. The primary advantage of this tool is its ability to convert static document content into dynamic audio content, allowing users to listen on mobile devices while also serving as a source of material for podcast episodes.

bleep_that_sht is an application written in Python that uses the Whisper transcription model to transcribe audio and then replace selected keywords, using corresponding timestamps with beeps. All processing is done locally, no data is uploaded, and user privacy is protected.

FoleyCrafter is a text-based video to audio generation framework capable of producing high-quality audio that is semantically relevant to the input video and time-synced. This technology holds significant importance in video production, especially during post-production, where it can greatly enhance efficiency and audio quality. It was jointly developed by the Shanghai Artificial Intelligence Laboratory and the Chinese University of Hong Kong, Shenzhen.

Suno-api is an open-source project designed to integrate the music generation AI from suno.ai via API calls, allowing users to easily incorporate the music generation feature into various AI intermediaries, like GPT. The project comes with an open-source license, facilitating free integration and modification, supports custom modes, allows users to set lyrics, music style, and titles, and can be deployed to Vercel with a single click.

QA-MDT is an open-source music generation model that integrates state-of-the-art models for music creation. It is based on various open-source projects, including AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. The QA-MDT model can generate high-quality music by utilizing diverse training strategies. It is particularly suitable for researchers and developers interested in music generation.

pdf-to-podcast is an AI-powered productivity tool that transforms PDF documents into podcast episodes. It utilizes OpenAI's text-to-speech model and Google Gemini technology to process PDF content into natural dialogue suitable for audio podcasts, outputting as MP3 files. The primary advantage of this tool is its ability to convert static document content into dynamic audio content, allowing users to listen on mobile devices while also serving as a source of material for podcast episodes.

Audio Isolation is an online audio processing service provided by ElevenLabs, dedicated to segregating vocals or background music from audio tracks. This technology is crucial for applications in music production and post-production video editing, significantly enhancing the efficiency and quality of audio editing. The service is provided via API, supports multiple programming languages, and offers high flexibility and ease of use. Pricing is based on the number of audio characters processed per minute, with specific costs not clearly indicated on the website.

bleep_that_sht is an application written in Python that uses the Whisper transcription model to transcribe audio and then replace selected keywords, using corresponding timestamps with beeps. All processing is done locally, no data is uploaded, and user privacy is protected.

FoleyCrafter is a text-based video to audio generation framework capable of producing high-quality audio that is semantically relevant to the input video and time-synced. This technology holds significant importance in video production, especially during post-production, where it can greatly enhance efficiency and audio quality. It was jointly developed by the Shanghai Artificial Intelligence Laboratory and the Chinese University of Hong Kong, Shenzhen.

Suno-api is an open-source project designed to integrate the music generation AI from suno.ai via API calls, allowing users to easily incorporate the music generation feature into various AI intermediaries, like GPT. The project comes with an open-source license, facilitating free integration and modification, supports custom modes, allows users to set lyrics, music style, and titles, and can be deployed to Vercel with a single click.

Lyria Music Generator is a state-of-the-art AI music generation model that empowers musicians and creators to craft incredible musical pieces. It generates high-quality music, including instruments and vocals, performs transformation and continuation tasks, and offers more refined style and performance control. In addition, there are two AI experimental projects: Dream Track and Music AI Tool, aimed at forging new frontiers for creativity.

AudioSep is an open-domain audio source separation model based on natural language queries. It consists of two key components: a text encoder and a separation model. We trained AudioSep on a large-scale multimodal dataset and extensively evaluated its capabilities on many tasks, including audio event separation, instrument separation, and voice enhancement. AudioSep demonstrates strong separation performance and impressive zero-shot generalization ability, significantly outperforming previous audio query and language query sound separation models when using audio titles or text labels as queries. To ensure the reproducibility of this work, we will release the source code, evaluation benchmark, and pre-trained models.