# Analysis of Phonetic Segments of Oesophageal Speech in People Following Total Laryngectomy
## 1 Introduction
A very common opinion among laryngectomized people is that oesophageal speech is the real one, in the natural sense--in contrast to the use of speech prosthesis [8; 9; 10]. The analysis of oesophageal speech can be carried out by examining the spoken vowels, consonants, whole words, or individual fragments of these words separately. In [2], the authors focused on the parameterization of oesophageal speech by examining the pronounced vowel \"i\". Patients uttered the same vowels repeatedly over a period of time. In the literature, different languages are considered when examining oesophageal speech. This is due to the fact that each language has inherently different characteristics that have a direct impact on the learning of oesophageal speech. This results from the particular articulation of consonants, vowels and individual words spoken in a particular language. In paper [4], the authors focused on the lexical tones of the Taiwanese language. This analysis took place in the time-frequency space of the signal. This research focused on the observation of changes in the fundamental frequency (F0), the slope of the F0 contour, and the duration and the amplitude of the vowels of parts of syllables containing seven Taiwanese tones. The study involved seven people undergoing speech rehabilitation after total laryngectomy [4]. In this paper, the acoustic analysis revealed no significant effects of the linguistic level on the acoustic parameters except for duration. This result seems justified due to the use of a small set of speech-signal physical characteristics of the speech signal. The authors in [8] attempted to improve the voice quality of oesophageal speech. In this case, working with time-, spectrum- and cepstrum-function descriptors aimed at improving the quality of oesophageal speech and thus increasing the effectiveness of communication. Available publications on the analysis of oesophageal speech prove that this analysis should take place in the time-frequency space and the cepstrum. In addition, the parameterization should take into account the language in which the test words are spoken. The study of oesophageal speech was also undertaken in [7]. The results of this analysis showed that the feature vectors obtained from the time domain, frequency domain, cepstrum and mel coefficients allow for precise parameterization of oesophageal speech. Audio features (including speech features) are extracted directly from the samples of the audio signal. Typical examples are the short-term energy and short-term zero-crossing rate. Such features offer a simple way to analyze audio signals, although it is usually necessary to combine them with more sophisticated frequency-domain features. Two approaches are possible:
* Based on the so-called signal macrostructure--calculations are performed in time segments after initial segmentation, the obtained parameters are the amplitude and rate of change;
* Based on the so-called the signal microstructure, i.e., the time course, analyzing the zero-crossing rate of the speech signal. This leads to obtaining two types of parameters: the density of zero crossings and the distribution of time intervals. The aim of the authors of this paper was to parameterize oesophageal speech using words that are used during the rehabilitation of patients following total laryngectomy. The studied patients were under the care of the Bydgoszcz Laryngectomy Association (Bydgoszcz, Poland), where they underwent speech rehabilitation. These people spoke Polish, so all the analyzed words were spoken in Polish. The choice of words was determined by the rehabilitation process and depends on the specificity of the Polish language (Figure 1) [11]. This study aimed to analyze oesophageal speech using the division of the examined words into phonetic segments (phonetic syllables). Phonetic segments are changes in loudness between consecutive sounds in a stream of speech sounds. The center of the phonetic segment is the voice segment that differs in loudness level from the immediate surroundings.