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Analysis of audio input to extract high-level meaning, intent, and context using neural models.
Distinct from Audio Indexers: Covers general semantic meaning and context extraction, which is broader than indexing or simple translation.
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Kimi-Audio is a large language model audio foundation model designed to understand audio input and generate high-fidelity speech responses in real time. It functions as a unified system encompassing a text-to-speech synthesis engine and a speech-to-text transcription tool. The project enables real-time audio conversations through a multi-modal conversation loop and chunk-wise streaming detokenization to reduce playback latency. It provides controls over speech speed, accent, and emotional tone during conversational audio generation. The system covers audio intelligence capabilities, includin
Analyzes audio clips to identify sounds, music, speech, and environmental scenes for classification or question answering.