Using Whisper for Speech Recognition in Elixir Applications

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Using Whisper for Speech Recognition in Elixir Applications
Sean Moriarity presents Bumblebee, a library for Elixir that allows developers to utilize pre-trained models such as GPT2, Stable Diffusion, ConvNext, and more. The latest inclusion to Bumblebee is Whisper from OpenAI, which specializes in transcription tasks through audio-speech recognition. Whisper's model is based on 680,000 hours of training across multiple languages, which helps it handle diverse accents and recognize jargon. It uses an audio encoder and a text-generating decoder for transforming speech into text. To use Whisper in Elixir, Bumblebee, Nx, EXLA dependencies need to be installed; an audio-processing pipeline is recommended, with ffmpeg being a requirement for audio to tensor processing. Once set up, Bumblebee enables Elixir applications to directly transcribe audio files and provides the potential to combine ASR with other models for summarization or classification tasks, offering a wide range of possible applications.

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