Purpose The purpose of this research note is to provide a performance comparison of available algorithms for the automated evaluation of oral diadochokinesis using speech samples from patients with amyotrophic lateral sclerosis (ALS). Method Four different algorithms based on a wide range of signal processing approaches were tested on a sequential motion rate /pa/-/ta/-/ka/ syllable repetition paradigm collected from 18 patients with ALS and 18 age- and gender-matched healthy controls (HCs). Results The best temporal detection of syllable position for a 10-ms tolerance value was achieved for ALS patients using a traditional signal processing approach based on a combination of filtering in the spectrogram, Bayesian detection, and polynomial thresholding with an accuracy rate of 74.4%, and for HCs using a deep learning approach with an accuracy rate of 87.6%. Compared to HCs, a slow diadochokinetic rate (p < .001) and diadochokinetic irregularity (p < .01) were detected in ALS patients. Conclusions The approaches using deep learning or multiple-step combinations of advanced signal processing methods provided a more robust solution to the estimation of oral DDK variables than did simpler approaches based on the rough segmentation of the signal envelope. The automated acoustic assessment of oral diadochokinesis shows excellent potential for monitoring bulbar disease progression in individuals with ALS.
- MeSH
- akustika MeSH
- algoritmy MeSH
- amyotrofická laterální skleróza * MeSH
- Bayesova věta MeSH
- lidé MeSH
- řeč MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Evaluation of precision of consonant articulation is commonly used metric in assessment of pathological speech. However, up to date most of the research on consonant characteristics was performed on English while there are obvious language-specific differences. The aim of the current study was therefore to investigate the patterns of consonant articulation in Czech across 6 stop consonants with respect to age and gender. The database used consisted of 30 female and 30 male healthy participants (mean age 51.0 years, standard deviation 18.0 years and range from 20 to 79 years). Four acoustic variables including voice onset time (VOT), VOT ratio and two spectral moments were analyzed. The Czech plosives /p/, /t/ and /k/ were found to be characterized by short voicing lag (average VOT ranged from 14 to 32 ms) while voiced plosives /b/, /d/ and /g/ by long voicing lead (average VOT ranged from -79 to -91 ms). Furthermore, we observed significantly longer duration of both VOT (p < 0.05) and VOT ratio (p < 0.01) of voiceless plosives in female compared to male gender. Finally, we revealed a significant negative correlation between age and duration of voiceless (r = -0.36, p < 0.05) as well as voiced VOT (r = -0.45, p = 0.01) in female but not in male participants.
Evaluation of precision of consonant articulation is commonly used metric in assessment of pathological speech. However, up to date most of the research on consonant characteristics was performed on English while there are obvious language-specific differences. The aim of the current study was therefore to investigate the patterns of consonant articulation in Czech across 6 stop consonants with respect to age and gender. The database used consisted of 30 female and 30 male healthy participants (mean age 51.0 years, standard deviation 18.0 years and range from 20 to 79 years). Four acoustic variables including voice onset time (VOT), VOT ratio and two spectral moments were analyzed. The Czech plosives /p/, /t/ and /k/ were found to be characterized by short voicing lag (average VOT ranged from 14 to 32 ms) while voiced plosives /b/, /d/ and /g/ by long voicing lead (average VOT ranged from -79 to -91 ms). Furthermore, we observed significantly longer duration of both VOT (p < 0.05) and VOT ratio (p < 0.01) of voiceless plosives in female compared to male gender. Finally, we revealed a significant negative correlation between age and duration of voiceless (r = -0.36, p < 0.05) as well as voiced VOT (r = -0.45, p = 0.01) in female but not in male participants.
- Klíčová slova
- akustická analýza,
- MeSH
- hlas MeSH
- kvalita hlasu * MeSH
- lidé MeSH
- poruchy artikulace MeSH
- věkové faktory MeSH
- výzkum MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
