Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. It uses a novel model setup that combines continuous acoustic features with discrete semantic tokens to richly capture sound and meaning across speech, music, and environmental audio.

Features

  • Universal audio foundation model
  • Automatic speech recognition (ASR)
  • Audio understanding and question answering
  • Speech emotion recognition and sound classification
  • End-to-end speech conversation support
  • Includes evaluation tools and pretrained models

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Additional Project Details

Programming Language

Python

Related Categories

Python AI Models

Registered

19 hours ago