import { DEFAULT_SESSION_OPTIONS, type OrtRuntime } from "./ort-runtime.js";
export interface SegmentationOptions {
    /** Window duration in seconds. pyannote/segmentation-3.0 was trained on 10s. */
    windowSec?: number;
    /** Window step (fraction of window). pyannote default is 0.1. */
    stepRatio?: number;
    /** Sample rate the model expects. */
    sampleRate?: number;
    /** Inference batch size. */
    batchSize?: number;
    /** Called after each batch with `(processed, total)` chunks. */
    onProgress?: (processed: number, total: number) => void;
    /** Sleep N ms between consecutive batches. Used to throttle GPU/CPU load. */
    batchYieldMs?: number;
}
export interface SegmentationResult {
    /** (numChunks, numFrames, numLocalSpeakers) hard activations from powerset argmax. */
    data: Uint8Array;
    numChunks: number;
    numFrames: number;
    numLocalSpeakers: number;
    windowSamples: number;
    stepSamples: number;
    frameDurationSec: number;
    chunkStarts: Float64Array;
}
export declare class SegmentationModel {
    private readonly session;
    private readonly ort;
    private readonly powerset;
    private readonly numLocalSpeakers;
    private readonly numPowersetClasses;
    private constructor();
    static load(modelSource: string | ArrayBufferLike | Uint8Array, ort: OrtRuntime, sessionOptions?: typeof DEFAULT_SESSION_OPTIONS): Promise<SegmentationModel>;
    run(waveform: Float32Array, options?: SegmentationOptions): Promise<SegmentationResult>;
    private runBatch;
}
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