import { VADAdapter, VADConfig, VADState, VADFactory, VADMetadata, VADEventEmitter } from '../';
/**
 * Smart Turn V3.2 Adapter Configuration
 */
export interface SmartTurnConfig extends VADConfig {
    /** Model URL override (defaults to CDN) */
    modelUrl?: string;
    /** Preferred backend ('webgpu', 'wasm', 'auto') */
    backend?: 'webgpu' | 'wasm' | 'auto';
    /** Maximum audio buffer duration in seconds (default: 8) */
    maxBufferDuration?: number;
    /** Run inference only when primary VAD detects silence (recommended) */
    useWithPrimaryVAD?: boolean;
    /** Primary VAD adapter ID (e.g., 'silero', 'simple') */
    primaryVADAdapter?: string;
    /** Confidence threshold for turn completion (0-1, default: 0.5) */
    completionThreshold?: number;
}
/**
 * Smart Turn VAD Adapter
 *
 * Implements semantic turn detection using PipeCat's Smart Turn v3.2 model.
 * Supports WebGPU acceleration with WASM fallback.
 */
export declare class SmartTurnAdapter extends VADEventEmitter implements VADAdapter {
    readonly id = "smart-turn";
    readonly name = "Smart Turn V3.2";
    readonly version = "3.2.0";
    private config;
    private state;
    private initialized;
    private backend;
    private session;
    private audioBuffer;
    private lastInferenceTime;
    private inferenceInterval;
    private inferenceInProgress;
    private speechStartTime;
    private static readonly MODEL_URL;
    constructor(config?: Partial<SmartTurnConfig>);
    /**
     * Initialize the Smart Turn adapter
     */
    initialize(): Promise<void>;
    /**
     * Initialize WebGPU or WASM backend
     */
    private initializeBackend;
    /**
     * Check if WebGPU is supported
     */
    private isWebGPUSupported;
    /**
     * Configure ONNX Runtime to load all WASM assets from CDN
     * This must be called before creating any inference sessions
     */
    private configureONNXRuntimeCDN;
    /**
     * Load ONNX Runtime from CDN or local import
     * Prefers CDN to avoid bundling the 64MB library
     */
    private loadONNXRuntime;
    /**
     * Load ONNX Runtime from CDN (unpkg)
     */
    private loadONNXRuntimeFromCDN;
    /**
     * Load ONNX model using onnxruntime-web
     */
    private loadModel;
    /**
     * Process audio frame
     *
     * Strategy:
     * 1. Accumulate audio in buffer (max 8 seconds)
     * 2. Run inference periodically (every 500ms)
     * 3. Return probability of turn completion
     */
    processFrame(frame: Float32Array, _timestamp: number): number | null;
    /**
     * Accumulate audio in buffer
     */
    private accumulateAudio;
    /**
     * Run Smart Turn inference asynchronously
     */
    private runInferenceAsync;
    configure(config: VADConfig): void;
    reset(): void;
    dispose(): void;
    isReady(): boolean;
    getState(): VADState;
    /**
     * Get current backend
     */
    getBackend(): 'webgpu' | 'wasm' | null;
}
/**
 * Smart Turn Factory
 */
export declare class SmartTurnFactory implements VADFactory {
    create(config?: Partial<SmartTurnConfig>): SmartTurnAdapter;
    getMetadata(): VADMetadata;
}
/**
 * Register Smart Turn adapter with VAD Registry
 *
 * This function ensures the SmartTurnAdapter is registered.
 * The adapter auto-registers when the module is imported, but this function
 * can be called explicitly to ensure registration.
 *
 * @returns void
 */
export declare function registerSmartTurnAdapter(): void;
//# sourceMappingURL=SmartTurnAdapter.d.ts.map