Sound Generation

LLMs can generate sounds and even music based on text prompts. LLMs are capable of turning audio into text and text into audio. There are several models that can do this, including:

• OpenAI's Whisper: Whisper is a powerful automatic speech recognition (ASR) system that can transcribe spoken language into text. It is trained on a large dataset of diverse audio and is capable of understanding multiple languages and accents. Whisper can be used for various applications, including transcription services, voice assistants, and accessibility tools.
• Google's AudioLM: AudioLM is a model developed by Google that can generate high-quality audio samples from text prompts. It uses a combination of language modeling and audio synthesis techniques to create realistic sounds and music. AudioLM can be used for applications such as music generation, sound effects creation, and audio content generation.
• Meta's Make-A-Track: Make-A-Track is a model developed by Meta that can generate music tracks from text descriptions. It uses a combination of deep learning techniques to create melodic and rhythmic patterns based on the input text. Make-A-Track can be used for applications such as music composition, soundtrack generation, and audio content creation.

ElevenLabs and other companies provide APIs to generate high-quality speech from text using advanced neural network models. These services can be used for applications such as voiceovers, audiobooks, and virtual assistants.