import RecognizeStream = require('../lib/recognize-stream');
import GeneratedSpeechToTextV1 = require('./v1-generated');
declare class SpeechToTextV1 extends GeneratedSpeechToTextV1 {
    static ERR_NO_CORPORA: string;
    static ERR_TIMEOUT: string;
    constructor(options: any);
    /**
     * Waits while corpora analysis status is 'being_processes', fires callback once the status is 'analyzed'
     *
     * Note: the code will throw an error in case there in no corpus in the customization
     *
     *
     * @param {Object} params The parameters
     * @param {String} params.customization_id - The GUID of the custom language model
     * @param {Number} [params.interval=5000] - (milliseconds) - how long to wait between status checks
     * @param {Number} [params.times=30] - maximum number of attempts
     * @param {Function} callback
     */
    whenCorporaAnalyzed(params: any, callback: any): void;
    /**
     * Use the recognize function with a single 2-way stream over websockets
     *
     * @param {Object} params The parameters
     * @return {RecognizeStream}
     */
    recognizeUsingWebSocket(params: any): RecognizeStream;
    recognize(params: any, callback: any): void | Promise<any>;
    /**
     * Waits while a customization status is 'pending' or 'training', fires callback once the status is 'ready' or 'available'.
     *
     * Note: the customization will remain in 'pending' status until at least one word corpus is added.
     *
     * See http://www.ibm.com/watson/developercloud/speech-to-text/api/v1/#list_models for status details.
     *
     * @param {Object} params The parameters
     * @param {String} params.customization_id - The GUID of the custom language model
     * @param {Number} [params.interval=5000] - (milliseconds) - how log to wait between status checks
     * @param {Number} [params.times=30] - maximum number of attempts
     * @param {Function} callback
     */
    whenCustomizationReady(params: any, callback: any): void;
}
export = SpeechToTextV1;