import argparse import logging import os import random import subprocess import torch import torchaudio import utils def run(exe_path, scp_path, out_dir, wave_len, num_outputs, remove_files, log_level): logging.basicConfig(level=log_level) for i in range(num_outputs): try: nyquist = 16000 // 2 high_freq = random.randint(1, nyquist) low_freq = random.randint(0, high_freq - 1) vtln_low = random.randint(low_freq + 1, high_freq - 1) vtln_high = random.randint(vtln_low + 1, high_freq - 1) vtln_warp_factor = random.uniform(0.0, 10.0) if random.random() < 0.3 else 1.0 except Exception: continue if not ((0.0 <= low_freq < nyquist) and (0.0 < high_freq <= nyquist) and (low_freq < high_freq)): continue if not (vtln_warp_factor == 1.0 or ((low_freq < vtln_low < high_freq) and (0.0 < vtln_high < high_freq) and (vtln_low < vtln_high))): continue inputs = { 'blackman_coeff': '%.4f' % (random.random() * 5), 'energy_floor': '%.4f' % (random.random() * 5), 'frame_length': '%.4f' % (float(random.randint(3, wave_len - 1)) / 16000 * 1000), 'frame_shift': '%.4f' % (float(random.randint(1, wave_len - 1)) / 16000 * 1000), 'high_freq': str(high_freq), 'htk_compat': utils.generate_rand_boolean(), 'low_freq': str(low_freq), 'num_mel_bins': str(random.randint(4, 8)), 'preemphasis_coefficient': '%.2f' % random.random(), 'raw_energy': utils.generate_rand_boolean(), 'remove_dc_offset': utils.generate_rand_boolean(), 'round_to_power_of_two': utils.generate_rand_boolean(), 'snip_edges': utils.generate_rand_boolean(), 'subtract_mean': utils.generate_rand_boolean(), 'use_energy': utils.generate_rand_boolean(), 'use_log_fbank': utils.generate_rand_boolean(), 'use_power': utils.generate_rand_boolean(), 'vtln_high': str(vtln_high), 'vtln_low': str(vtln_low), 'vtln_warp': '%.4f' % (vtln_warp_factor), 'window_type': utils.generate_rand_window_type() } fn = 'fbank-' + ('-'.join(list(inputs.values()))) out_fn = out_dir + fn + '.ark' arg = [exe_path] arg += ['--' + k.replace('_', '-') + '=' + inputs[k] for k in inputs] arg += ['--dither=0.0', scp_path, out_fn] logging.info(fn) logging.info(inputs) logging.info(' '.join(arg)) try: if log_level == 'INFO': subprocess.call(arg) else: subprocess.call(arg, stderr=open(os.devnull, 'wb'), stdout=open(os.devnull, 'wb')) logging.info('success') except Exception: if remove_files and os.path.exists(out_fn): os.remove(out_fn) def decode(fn, sound_path, exe_path, scp_path, out_dir): """ Takes a filepath and prints out the corresponding shell command to run that specific kaldi configuration. It also calls compliance.kaldi and prints the two outputs. Example: >> fn = 'fbank-1.1009-2.5985-1.1875-0.8750-5723-true-918-4-0.31-true-false-true-true-' \ 'false-false-false-true-4595-4281-1.0000-hamming.ark' >> decode(fn) """ out_fn = out_dir + fn fn = fn[len('fbank-'):-len('.ark')] arr = [ 'blackman_coeff', 'energy_floor', 'frame_length', 'frame_shift', 'high_freq', 'htk_compat', 'low_freq', 'num_mel_bins', 'preemphasis_coefficient', 'raw_energy', 'remove_dc_offset', 'round_to_power_of_two', 'snip_edges', 'subtract_mean', 'use_energy', 'use_log_fbank', 'use_power', 'vtln_high', 'vtln_low', 'vtln_warp', 'window_type'] fn_split = fn.split('-') assert len(fn_split) == len(arr), ('Len mismatch: %d and %d' % (len(fn_split), len(arr))) inputs = {arr[i]: utils.parse(fn_split[i]) for i in range(len(arr))} # print flags for C++ s = ' '.join(['--' + arr[i].replace('_', '-') + '=' + fn_split[i] for i in range(len(arr))]) logging.info(exe_path + ' --dither=0.0 --debug-mel=true ' + s + ' ' + scp_path + ' ' + out_fn) logging.info() # print args for python inputs['dither'] = 0.0 logging.info(inputs) sound, sample_rate = torchaudio.load_wav(sound_path) kaldi_output_dict = {k: v for k, v in torchaudio.kaldi_io.read_mat_ark(out_fn)} res = torchaudio.compliance.kaldi.fbank(sound, **inputs) torch.set_printoptions(precision=10, sci_mode=False) logging.info(res) logging.info(kaldi_output_dict['my_id']) if __name__ == '__main__': """ Examples: >> python test/compliance/generate_fbank_data.py \ --exe_path=/scratch/jamarshon/kaldi/src/featbin/compute-fbank-feats \ --scp_path=scp:/scratch/jamarshon/downloads/a.scp \ --out_dir=ark:/scratch/jamarshon/audio/test/assets/kaldi/ >> python test/compliance/generate_fbank_data.py \ --exe_path=/scratch/jamarshon/kaldi/src/featbin/compute-fbank-feats \ --scp_path=scp:/scratch/jamarshon/downloads/a.scp \ --out_dir=ark:/scratch/jamarshon/audio/test/assets/kaldi/ \ --decode=true \ --sound_path=/scratch/jamarshon/audio/test/assets/kaldi_file.wav \ --fn="fbank-1.1009-2.5985-1.1875-0.8750-5723-true-918-4-0.31-true-false-true- true-false-false-false-true-4595-4281-1.0000-hamming.ark" """ parser = argparse.ArgumentParser(description='Generate fbank data using Kaldi.') parser.add_argument('--exe_path', type=str, required=True, help='Path to the compute-fbank-feats executable.') parser.add_argument('--scp_path', type=str, required=True, help='Path to the scp file. An example of its contents would be \ "my_id /scratch/jamarshon/audio/test/assets/kaldi_file.wav". where the space separates an id from a wav file.') parser.add_argument('--out_dir', type=str, required=True, help='The directory to which the stft features will be written to.') # run arguments parser.add_argument('--wave_len', type=int, default=20, help='The number of samples inside the input wave file read from `scp_path`') parser.add_argument('--num_outputs', type=int, default=100, help='How many output files should be generated.') parser.add_argument('--remove_files', type=bool, default=False, help='Whether to remove files generated from exception') parser.add_argument('--log_level', type=str, default='WARNING', help='Log level (DEBUG|INFO|WARNING|ERROR|CRITICAL)') # decode arguments parser.add_argument('--decode', type=bool, default=False, help='Whether to run the decode or run function.') parser.add_argument('--fn', type=str, help='Filepath to decode.') parser.add_argument('--sound_path', type=str, help='Sound filepath to decode.') args = parser.parse_args() if args.decode: decode(args.fn, args.sound_path, args.exe_path, args.scp_path, args.out_dir) else: run(args.exe_path, args.scp_path, args.out_dir, args.wave_len, args.num_outputs, args.remove_files, args.log_level)