{'fraction_non_alphanumeric': 0.013422818791946308, 'fraction_numerical': 0.0, 'mean_word_length': 5.069767441860465, '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}}
Analysis and synthesis of speech based on spectral transform linear predictive method

The Linear Predictive (LP) method has been widely used in speech analysis, mainly because of the simple mathematical formulation of the model and the straightforward computation of its parameters. However, there still remain certain difficulties that cause errors in the result of the analysis. Often encountered are the errors due to harmonic structure of the excitation source. The Spectral Transform LP (STLP) method proposed in the present paper aims at reducing these errors. Amplitude transforms on the input spectrum and on the spectrum of the model are introduced to modify the error criterion and the model adopted in the standard LP analysis. We show by analyses of both synthetic and natural speech that the STLP method offers significant improvement over the standard LP method. A method of STLP speech synthesis using the standard LP model is proposed. A perceptual experiment confirms the superiority of the STLP method in analysis of speech.