import { VadDetector, VadDetectorResult } from "../../types/streaming/dual-channel";
export type EnergyVadParams = {
    /** Threshold = noiseFloor * thresholdRatio. Default 3.0 (~ +9.5 dB above noise). */
    thresholdRatio?: number;
    /** EMA smoothing for the noise-floor estimate when frame is non-speech. Default 0.05. */
    noiseFloorAlpha?: number;
    /** Hangover in frames: stay "active" this many frames after the last speech frame. Default 10 (\~200 ms at 20 ms frames). */
    hangoverFrames?: number;
    /** Initial noise floor estimate. Default 1e-4. Adaptive after the first non-speech frame. */
    initialNoiseFloor?: number;
};
/**
 * Energy-based VAD with adaptive noise-floor tracking and hangover. Pure JS,
 * no dependencies. Suitable for the "which physical channel is speaking" task
 * because the channels are already physically separated at capture — the harder
 * problem (speech vs. non-speech in the wild) is one a customer can swap in a
 * DNN VAD for via the `createVad` parameter.
 *
 * Tuning notes:
 * - thresholdRatio below 2 will treat anything above noise as speech (too sensitive).
 * - thresholdRatio above 6 will miss quiet utterance onsets/offsets.
 * - noiseFloorAlpha above 0.1 makes the floor track quickly (good for non-stationary
 *   background) but risks slowly adapting *up* to a sustained low voice.
 */
export declare class EnergyVad implements VadDetector {
    private readonly thresholdRatio;
    private readonly noiseFloorAlpha;
    private readonly hangoverFrames;
    private readonly initialNoiseFloor;
    private noiseFloor;
    private hangoverRemaining;
    constructor(params?: EnergyVadParams);
    process(frame: Float32Array): VadDetectorResult;
    reset(): void;
}