jamie@1: /* libxtract feature extraction library
jamie@1:  *  
jamie@1:  * Copyright (C) 2006 Jamie Bullock
jamie@1:  *
jamie@1:  * This program is free software; you can redistribute it and/or modify
jamie@1:  * it under the terms of the GNU General Public License as published by
jamie@1:  * the Free Software Foundation; either version 2 of the License, or
jamie@1:  * (at your option) any later version.
jamie@1:  *
jamie@1:  * This program is distributed in the hope that it will be useful,
jamie@1:  * but WITHOUT ANY WARRANTY; without even the implied warranty of
jamie@1:  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
jamie@1:  * GNU General Public License for more details.
jamie@1:  *
jamie@1:  * You should have received a copy of the GNU General Public License
jamie@1:  * along with this program; if not, write to the Free Software
jamie@1:  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, 
jamie@1:  * USA.
jamie@1:  */
jamie@1: 
jamie@1: /* xtract_scalar.h: declares functions that extract a feature as a single value from an input vector */
jamie@1: 
jamie@1: #ifndef XTRACT_SCALAR
jamie@1: #define XTRACT_SCALAR
jamie@1: 
jamie@1: #ifdef __cplusplus
jamie@1: extern "C" {
jamie@1: #endif
jamie@1: 
jamie@1: 
jamie@1: /* Statistical features */
jamie@1: 
jamie@1: int xtract_mean(float *data, int N, void *argv, float *result);
jamie@1: /* mean is passed in as arg */
jamie@1: int xtract_variance(float *data, int N, void *argv, float *result);
jamie@1: /* variance is passed in as arg */
jamie@1: int xtract_standard_deviation(float *data, int N, void *argv, float *result);
jamie@1: /* mean is passed in as arg */
jamie@1: int xtract_average_deviation(float *data, int N, void *argv, float *result);
jamie@1: /* mean and standard deviation are passed in as arg */
jamie@1: int xtract_skewness(float *data, int N, void *argv,  float *result);
jamie@1: /* mean and standard deviation are passed in as arg */
jamie@1: int xtract_kurtosis(float *data, int N, void *argv,  float *result);
jamie@1: 
jamie@1: /* Irregularity */
jamie@1: 
jamie@1: /* Krimphoff (1994) */
jamie@1: int xtract_irregularity_k(float *data, int N, void *argv, float *result);
jamie@1: /* Jensen (1999) */
jamie@1: int xtract_irregularity_j(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Tristimulus */
jamie@1: 
jamie@1: /* Pollard and Jansson (1982) */
jamie@1: int xtract_tristimulus_1(float *data, int N, void *argv, float *result);
jamie@1: int xtract_tristimulus_2(float *data, int N, void *argv, float *result);
jamie@1: int xtract_tristimulus_3(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Smoothness */
jamie@1: 
jamie@1: /*McAdams (1999)*/
jamie@1: int xtract_smoothness(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Spectral Spread */
jamie@1: 
jamie@1: /* Casagrande 2005 */
jamie@1: 
jamie@1: int xtract_spread(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Zero crossing rate */
jamie@1: 
jamie@1: int xtract_zcr(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Rolloff */
jamie@1: 
jamie@1: /* Bee Suan Ong (2005) */
jamie@1: /* Threshold is the percentile at which the rolloff is determined */
jamie@1: 
jamie@1: int xtract_rolloff(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Loudness */
jamie@1: /* A set of BARK_BANDS bark coefficients must be passed in, the loudness is calculated approximately according to Moore, Glasberg et al, 1997 */
jamie@1: 
jamie@1: int xtract_loudness(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Spectral Flatness Measure */
jamie@1: /* Tristan Jehan (2005) */
jamie@1: 
jamie@1: int xtract_flatness(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Tonality Factor */
jamie@1: /* Tristan Jehan (2005) */
jamie@1: 
jamie@1: int xtract_tonality(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Noisiness */
jamie@1: /* Tae Hong Park (2000) */
jamie@1: 
jamie@1: int xtract_noisiness(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* RMS amplitude */
jamie@1: /* Tae Hong Park (2000) */
jamie@1: 
jamie@1: int xtract_rms_amplitude(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Inharmonicity */
jamie@1: 
jamie@1: int xtract_inharmonicity(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Spectral Crest */
jamie@1: /* Peeters (2003) */
jamie@1: int xtract_crest(float *data, int N, void *argv, float *result);
jamie@1:     
jamie@1: /* Spectral Power */
jamie@1: /* Bee Suan Ong (2005) */
jamie@1: int xtract_power(float *data, int N, void *argv, float *result);
jamie@1:     
jamie@1: /* Odd to even harmonic ratio */
jamie@1: 
jamie@1: int xtract_odd_even_ratio(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Sharpness */
jamie@1: 
jamie@1: int xtract_sharpness(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Slope */
jamie@1: int xtract_slope(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* F0 */
jamie@1: /*This method takes a guess which can come from taking the ZCR of an autocorrelation function, and then finds the spectral peak that most closely matches the gess */
jamie@1: int xtract_f0(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: /* Pitch */
jamie@1: /* Pitch via HPS analysis */
jamie@1: int xtract_hps(float *data, int N, void *argv, float *result);
jamie@1: 
jamie@1: #ifdef __cplusplus
jamie@1: }
jamie@1: #endif
jamie@1: 
jamie@1: #endif
jamie@1: 
jamie@1: 
jamie@1: