/**
 * Approximate STFT magnitude from a Mel power spectrogram.
 *
 * NOTE: an exact inverse solves a non-negative least squares problem
 * (nnls(mel_basis, M)); this implementation uses the filterbank TRANSPOSE as
 * a pseudo-inverse — a rough approximation. Spectral shape (per-frame peak
 * location, cosine similarity vs |stft|) survives; absolute magnitudes do not.
 * @param {Array} M - Mel spectrogram [n_mels x n_frames]
 * @param {number} sr - Sample rate
 * @param {number} n_fft - FFT size
 * @param {number} power - Power for the spectrogram (2.0 for power, 1.0 for magnitude)
 * @param {Object} kwargs - Additional arguments for mel_filterbank
 * @returns {Array} Approximate STFT magnitude [n_freq x n_frames]
 */
export function mel_to_stft(M: any[], sr?: number, n_fft?: number, power?: number, kwargs?: any): any[];
/**
 * Invert a mel power spectrogram to audio using Griffin-Lim
 * @param {Array} M - Mel spectrogram [n_mels x n_frames]
 * @param {number} sr - Sample rate
 * @param {number} n_fft - FFT size
 * @param {number} hop_length - Hop length
 * @param {number} win_length - Window length
 * @param {string} window - Window type
 * @param {boolean} center - Center the frames
 * @param {string} pad_mode - Padding mode
 * @param {number} power - Power for spectrogram (2.0 for power, 1.0 for magnitude)
 * @param {number} n_iter - Number of Griffin-Lim iterations
 * @param {number|null} length - Output length
 * @param {*} dtype - Data type (unused in JS)
 * @param {Object} kwargs - Additional mel_filterbank arguments
 * @returns {Float32Array} Reconstructed audio
 */
export function mel_to_audio(M: any[], sr?: number, n_fft?: number, hop_length?: number, win_length?: number, window?: string, center?: boolean, pad_mode?: string, power?: number, n_iter?: number, length?: number | null, dtype?: any, kwargs?: any): Float32Array;
/**
 * Invert Mel-frequency cepstral coefficients to approximate a Mel power spectrogram
 * @param {Array} mfcc - MFCC matrix [n_mfcc x n_frames]
 * @param {number} n_mels - Number of Mel filters
 * @param {number} dct_type - DCT type (2 or 3)
 * @param {string|null} norm - DCT normalization
 * @param {number} ref - Reference value for dB conversion
 * @param {number} lifter - Liftering coefficient (0 to disable)
 * @returns {Array} Mel power spectrogram [n_mels x n_frames]
 */
export function mfcc_to_mel(mfcc: any[], n_mels?: number, dct_type?: number, norm?: string | null, ref?: number, lifter?: number): any[];
/**
 * Convert Mel-frequency cepstral coefficients to a time-domain audio signal
 * @param {Array} mfcc - MFCC matrix [n_mfcc x n_frames]
 * @param {number} n_mels - Number of Mel filters
 * @param {number} dct_type - DCT type
 * @param {string|null} norm - DCT normalization
 * @param {number} ref - Reference value for dB conversion
 * @param {number} lifter - Liftering coefficient
 * @param {Object} kwargs - Additional arguments for mel_to_audio
 * @returns {Float32Array} Reconstructed audio
 */
export function mfcc_to_audio(mfcc: any[], n_mels?: number, dct_type?: number, norm?: string | null, ref?: number, lifter?: number, kwargs?: any): Float32Array;