Improving the quality of speech in the conditions of noise and interference

Abstract

The aim of the work is to present a method of intelligent modification of the speech signal with speech features expressed in noise, based on the Lombard effect. The recordings utilized sets of words and sentences as well as disturbing signals, i.e., pink noise and the so-called babble speech. Noise signal, calibrated to various levels at the speaker's ears, was played over two loudspeakers located 2 m away from the speaker. In addition, the recording session included utterances in quiet, which constitute a reference to the received speech signal analysis with the Lombard effect. As a part of the analysis, the following parameters were examined with regard to prosody: fundamental frequency F0, formant frequencies of F1 and F2, duration of the utterance, sound intensity, etc., taking into account individual sentences, words, and vowels. The PRAAT program was used to process and analyze speech signals. Next, a method for modifying speech with the features of speech spoken in noise was proposed. Subsequent analyzes have shown that noisy speech modified by the Lombard effect features is characterized by higher values of the PESQ (perceptual evaluation of speech quality) speech quality indicator compared to noisy speech without the features incorporated.The aim of the work is to present a method of intelligent modification of the speech signal with speech features expressed in noise, based on the Lombard effect. The recordings utilized sets of words and sentences as well as disturbing signals, i.e., pink noise and the so-called babble speech. Noise signal, calibrated to various levels at the speaker's ears, was played over two loudspeakers located 2 m away from the speaker. In addition, the recording session included utterances in quiet, which constitute a reference to the received speech signal analysis with the Lombard effect. As a part of the analysis, the following parameters were examined with regard to prosody: fundamental frequency F0, formant frequencies of F1 and F2, duration of the utterance, sound intensity, etc., taking into account individual sentences, words, and vowels. The PRAAT program was used to process and analyze speech signals. Next, a method for modifying speech with the features of speech spoken in noise was proposed. Subsequent a...