{'fraction_non_alphanumeric': 0.024572649572649572, 'fraction_numerical': 0.009615384615384616, 'mean_word_length': 5.462068965517242, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
On properties of modulation spectrum for robust automatic speech recognition

We report on the effect of band-pass filtering of the time trajectories of spectral envelopes on speech recognition. Several types of filter (linear-phase FIR, DCT, and DFT) are studied. Results indicate the relative importance of different components of the modulation spectrum of speech for ASR. General conclusions are: (1) most of the useful linguistic information is in modulation frequency components from the range between 1 and 16 Hz, with the dominant component at around 4 Hz, (2) it is important to preserve the phase information in the modulation frequency domain, (3) the features which include components at around 4 Hz in the modulation spectrum outperform the conventional delta features, (4) the features which represent the several modulation frequency bands with appropriate center frequency and bandwidth increase recognition performance.