From 8550ac7954861df17916a416cb70fc22742a6ecd Mon Sep 17 00:00:00 2001 From: "jordi.hasianta" Date: Thu, 15 Sep 2022 21:34:08 +0700 Subject: [PATCH] fix code refactoring in intensity --- .../raw_features/audio/intensity.py | 153 ++++++------------ 1 file changed, 47 insertions(+), 106 deletions(-) diff --git a/opendbm/dbm_lib/dbm_features/raw_features/audio/intensity.py b/opendbm/dbm_lib/dbm_features/raw_features/audio/intensity.py index 7601da14..33d3b18a 100644 --- a/opendbm/dbm_lib/dbm_features/raw_features/audio/intensity.py +++ b/opendbm/dbm_lib/dbm_features/raw_features/audio/intensity.py @@ -1,15 +1,13 @@ """ -file_name: gne +file_name: intensity project_name: DBM created: 2020-20-07 """ import glob import logging -import os from os.path import join -import more_itertools as mit import numpy as np import pandas as pd import parselmouth @@ -19,115 +17,67 @@ from opendbm.dbm_lib.dbm_features.raw_features.util import util as ut logging.basicConfig(level=logging.INFO) logger = logging.getLogger() -gne_dir = "acoustic/glottal_noise" -ff_dir = "acoustic/pitch" -csv_ext = "_gne.csv" +intensity_dir = "acoustic/intensity" +csv_ext = "_intensity.csv" +error_txt = "error: length less than 0.064" -def gne_ratio(sound): +def intensity_score(path): """ - Using parselmouth library fetching glottal noise excitation ratio + Using parselmouth library fetching Intensity Args: - sound: parselmouth object + path: (.wav) audio file location Returns: - (list) list of gne ratio for each voice frame + (list) list of Intensity for each voice frame """ - harmonicity_gne = sound.to_harmonicity_gne() - gne_all_bands = harmonicity_gne.values - gne_all_bands = np.where(gne_all_bands == -200, np.NaN, gne_all_bands) - - gne = np.nanmax( - gne_all_bands - ) # following http://www.fon.hum.uva.nl/rob/NKI_TEVA/TEVA/HTML/NKI_TEVA.pdf - return gne + sound_pat = parselmouth.Sound(path) + intensity = sound_pat.to_intensity(time_step=0.001) + return intensity.values[0] -def empty_gne(video_uri, out_loc, fl_name, r_config, error_txt, save=True): +def calc_intensity(video_uri, audio_file, out_loc, fl_name, r_config, save=True): """ - Preparing empty GNE matrix if something fails - """ - cols = ["Frames", r_config.aco_gne, r_config.err_reason] - out_val = [[np.nan, np.nan, error_txt]] - - df_gne = pd.DataFrame(out_val, columns=cols) - df_gne["dbm_master_url"] = video_uri - - if save: - logger.info("Saving Output file {} ".format(out_loc)) - ut.save_output(df_gne, out_loc, fl_name, gne_dir, csv_ext) - return df_gne - - -def segment_gne(com_speech_sort, voiced_yes, voiced_no, gne_all_frames, audio_file): - """ - calculating gne for each voice segment - """ - snd = parselmouth.Sound(audio_file) - pitch = snd.to_pitch(time_step=0.001) - - for idx, vs in enumerate(com_speech_sort): - try: - - max_gne = np.NaN - if vs in voiced_yes and len(vs) > 1: - - start_time = pitch.get_time_from_frame_number(vs[0]) - end_time = pitch.get_time_from_frame_number(vs[-1]) - - snd_start = int(snd.get_frame_number_from_time(start_time)) - snd_end = int(snd.get_frame_number_from_time(end_time)) - - samples = parselmouth.Sound(snd.as_array()[0][snd_start:snd_end]) - max_gne = gne_ratio(samples) - except: - pass - - gne_all_frames[idx] = max_gne - return gne_all_frames - - -def calc_gne(video_uri, audio_file, out_loc, fl_name, r_config, save=True, ff_df=None): - """ - Preparing gne matrix + Preparing Intensity matrix Args: audio_file: (.wav) parsed audio file out_loc: (str) Output directory for csv's """ - dir_path = os.path.join(out_loc, ff_dir) - if os.path.isdir(dir_path) or ff_df is not None: - if ff_df is not None: - voice_seg = ut.process_segment_pitch(ff_df, r_config) - else: - voice_seg = ut.segment_pitch(dir_path, r_config, ff_df=ff_df) - gne_all_frames = [np.NaN] * len(voice_seg[0]) - gne_segment_frames = segment_gne( - voice_seg[0], voice_seg[1], voice_seg[2], gne_all_frames, audio_file - ) + intensity_frames = intensity_score(audio_file) + df_intensity = pd.DataFrame(intensity_frames, columns=[r_config.aco_int]) - df_gne = pd.DataFrame(gne_segment_frames, columns=[r_config.aco_gne]) - df_gne[ - r_config.err_reason - ] = "Pass" # will replace with threshold in future release + df_intensity["Frames"] = df_intensity.index + df_intensity["dbm_master_url"] = video_uri + df_intensity[ + r_config.err_reason + ] = "Pass" # will replace with threshold in future release - df_gne["Frames"] = df_gne.index - df_gne["dbm_master_url"] = video_uri - - if save: - logger.info("Processing Output file {} ".format(out_loc)) - ut.save_output(df_gne, out_loc, fl_name, gne_dir, csv_ext) - return df_gne - - else: - error_txt = "error: pitch freq not available" - return empty_gne(video_uri, out_loc, fl_name, r_config, error_txt, save=save) + if save: + logger.info("Saving Output file {} ".format(out_loc)) + ut.save_output(df_intensity, out_loc, fl_name, intensity_dir, csv_ext) + return df_intensity -def run_gne(video_uri, out_dir, r_config, save=True, ff_df=None): +def empty_intensity(video_uri, out_loc, fl_name, r_config, save=True): """ - Processing all patient's for fetching glottal noise ratio - --------------- - --------------- + Preparing empty Intensity matrix if something fails + """ + cols = ["Frames", r_config.aco_int, r_config.err_reason] + out_val = [[np.nan, np.nan, error_txt]] + df_int = pd.DataFrame(out_val, columns=cols) + df_int["dbm_master_url"] = video_uri + + if save: + logger.info("Saving Output file {} ".format(out_loc)) + ut.save_output(df_int, out_loc, fl_name, intensity_dir, csv_ext) + return df_int + + +def run_intensity(video_uri, out_dir, r_config, save=True): + """ + Processing all patient's for fetching Intensity + ------------------- + ------------------- Args: video_uri: video path; r_config: raw variable config object out_dir: (str) Output directory for processed output @@ -146,21 +96,12 @@ def run_gne(video_uri, out_dir, r_config, save=True, ff_df=None): "Output file {} size is less than 0.064sec".format(audio_file) ) - error_txt = "error: length less than 0.064" - df = empty_gne( - video_uri, out_loc, fl_name, r_config, error_txt, save=save - ) + df = empty_intensity(video_uri, out_loc, fl_name, r_config, save=save) else: - df = calc_gne( - video_uri, - audio_file, - out_loc, - fl_name, - r_config, - save=save, - ff_df=ff_df, + df = calc_intensity( + video_uri, audio_file, out_loc, fl_name, r_config, save=save ) - return df + return df except Exception as e: e logger.error("Failed to process audio file")