{'fraction_non_alphanumeric': 0.016580310880829015, 'fraction_numerical': 0.0051813471502590676, 'mean_word_length': 5.851063829787234, '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}}
Research on Adaptive Speaker Identification Based on GMM

In this paper, an adaptive speaker identification method combined with the human behavioral trait based on Gaussian mixture model (GMM) is constructed. The method can automatically select different length of speech for different speakers in identification process according to the feedback probability estimation, so it can guarantee identification accuracy without reducing, and to reduce the identification time significantly. This method reduces the identification time through two aspects: speaker acoustic features extraction and recognition probability estimation. Experiment results show that for 50 speakers identification, the identification time can reduce 4 times and the identification accuracy can reach 97%. Especially, the new method is fit for large population of speaker identification. From the analysis of this text, we can see that identification time will be reduced more substantially.