**9. Conclusion**

The methods described in this chapter were developed to analyze disordered speech in children, specifically in children with language impairments. The research was conducted over 10 years. The description is focused on the classification, data collection and data analysis of these children. For analysis, only speech skills of children with SLI were used and compared with typical children. The main benefit of this study includes the methods that were developed to classify children with SLI based on direct database processing. The implementation of these approaches in clinical practice could elucidate the progression and treatment of the disease and facilitate efficient disease treatment.

The first method, called error analysis, is based on the number of pronunciation errors in the utterances. A significant advantage is that its function does not require complex computational methods and can be performed by anyone. The success rate in distinguishing between children with SLI and typical children was 93.81%. The second method, called feature analysis, is based on the auditory signal features that are specific to the acoustic features of speech. These features can easily be obtained and calculated without complicated modifications of the speech signal. The success rate was 96.94%, and only three out of 98 participants were classified as incorrect. The third approach, based on the time duration of utterances, verified the hypotheses on the speed of processing and response for a range of tasks. Children with SLI have a longer duration of words than typical children, that is, the difference was 27.51%. In formant analysis, each vowel has a clearly defined location in the vocalic triangle. The difference between children with SLI and typical children is in the possibility (for typical children) or inability (for children with SLI) to create two vocalic triangles. The vocalic triangle for vowels from a multisyllabic word is misshapen in 87.5% of the analyses of children with SLI. The tablet application SLIt Tool uses an algorithm derived from error analysis, which facilitates the testing of children. The output verifies speech skills with possible consultation about the results via email with a speech and language pathologist.

The obtained results demonstrate that it is possible for children with SLI to be clearly identified and distinguished from typical children. The approach combined traditional and alternative procedures to address this issue and generated a resistance tool that is not dependent on the weaknesses of individual methods.

## **Acknowledgements**

The research has been supported by the Ministry of Health of the Czech Republic, grant no. IGA MZ CRNT11443-5/2010 and grant no. IGA MZ ČR-NR 8287-3/2005. This chapter has been supported by R&D Laboratory at the Military Technical Institute. The authors would like to thank the speech and language therapists, especially PaedDr. Milena Vránová, who tested our application. We would also like to thank American Journal Experts for their thoughtful English corrections.
