comparison xtract/xtract_scalar.h @ 1:b8f2448f7207

Initial import

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