MoonshotAI/Kimi-Audio

Features

• Unified Audio-Text Transformers - Processes speech and text tokens in a shared embedding space using a single transformer for seamless modality switching.
• Multi-Turn Speech Conversations - Maintains context across multiple spoken exchanges, generating both text and audio replies.
• Rolling Context Windows - Maintains a rolling context window of audio and text exchanges to support coherent multi-turn spoken dialogue.
• End-to-End Speech Conversations - Engages in a spoken dialogue that understands audio input and responds with both text and synthesized speech.
• Spoken Dialogue Systems - Ships a real-time spoken dialogue system that both understands audio input and generates speech responses.
• Text-to-Speech Response Generators - Produces high-fidelity spoken audio replies from text or conversational context in real time.
• LoRA Fine-Tuning Pipelines - Ships a LoRA-style fine-tuning pipeline for adapting pre-trained audio models to custom tasks on user-provided audio-text pairs.
• Audio - Loads a pretrained audio foundation model and runs inference on audio inputs to produce speech responses.
• Real-Time Speech Synthesis - Processes an audio stream and produces natural-sounding speech output in real time for conversational use.
• Speech to Text Transcription - Converts spoken audio into written text with high accuracy across multiple languages and acoustic conditions.
• Audio Chat Interfaces - Accepts spoken questions or commands and returns relevant text-based responses in a conversational format.
• Text-to-Speech - Ships a flow-matching detokenizer and vocoder for high-fidelity text-to-speech synthesis.
• Audio Semantic Token Extractors - Encodes raw audio into discrete semantic tokens via a pretrained encoder for efficient downstream processing.
• High-Fidelity Speech Synthesis - Produces natural-sounding spoken audio from text or semantic tokens using a flow-matching detokenizer.
• Generative Audio Chunking - Generates audio in small overlapping chunks and plays incrementally to minimize end-to-end latency during conversation.
• Speech Transcription Engines - Converts spoken audio input into accurate text output using a state-of-the-art speech recognition model.
• Neural Vocoders - Implements a flow-matching neural vocoder that converts semantic token sequences into high-fidelity raw audio waveforms.
• Audio Semantic Understanding - Analyzes audio clips to identify sounds, music, speech, and environmental scenes for classification or question answering.
• Audio Understanding Fine-Tuning - Trains a pretrained model on custom audio understanding data, such as automatic speech recognition, to adapt it to specific domains.
• Controllable Speech Generation - Adjusts the speed, accent, emotion, and style of generated speech to match desired expressive qualities.
• Custom Data Fine-Tunings - Adapts the pre-trained model to new tasks or domains by training on user-provided audio and text pairs.
• Audio Performance Benchmarks - Ships a benchmarking harness with standardized metrics and side-by-side inference recipes for audio models.
• Model Fine-Tuning - Adapts the pre-trained audio foundation model to custom domains or tasks using provided lightweight training code.
• Audio - Adapts the pre-trained audio foundation model to custom tasks or domains using lightweight fine-tuning scripts.
• Controllable Speech Conversations - Provides controls over speaking speed, accent, emotion, and style during conversational audio generation.
• Audio Question Answering - Responds to natural-language queries about the content of an audio clip, such as identifying sounds or answering factual questions.
• Audio Event Classification - Identifies audio categories such as speech, music, or environmental sounds from a clip.
• Audio Emotion Classifiers - Detects the emotional tone of a speaker's voice from an audio recording.
• Audio Content Analysis - Generates natural-language descriptions of audio clip content automatically.
• Side-by-Side Inference Recipes - Provides standardized inference recipes and metric calculators for reproducible side-by-side evaluation of audio foundation models.

Star history