Auswahl der wissenschaftlichen Literatur zum Thema „Rozpoznání hlasu“

The aim of the diploma thesis was to create a program with which it will be possible to control a collaborative robot by voice. First chapters contain a search of the current state in the field of collaborative robotics in terms of safety, work efficiency, robot programming and communication with the robot. Furthermore, the issue of machine processing of the human voice is discussed. In practical part was proposed an experiment in which we work with off-line simulation of UR3 robot in PolyScope 3.15.0 software. This simulation was linked to a Python program which uses SpeechRecognition and urx libraries. Simple voice instructions have been designed to move robot to defined position.

This work deals with the text-dependent speaker recognition in systems, where just a few training samples exist. For the purpose of this recognition, the voice imprint based on different features (e.g. MFCC, PLP, ACW etc.) is proposed. At the beginning, there is described the way, how the speech signal is produced. Some speech characteristics important for speaker recognition are also mentioned. The next part of work deals with the speech signal analysis. There is mentioned the preprocessing and also the feature extraction methods. The following part describes the process of speaker recognition and mentions the evaluation of the used methods: speaker identification and verification. Last theoretically based part of work deals with the classifiers which are suitable for the text-dependent recognition. The classifiers based on fractional distances, dynamic time warping, dispersion matching and vector quantization are mentioned. This work continues by design and realization of system, which evaluates all described classifiers for voice imprint based on different features.

The thesis deals with using the human voice for controlling electrical appliances by means of wireless technology. It concerns recognition of individual isolated words which form commands. A method based on the distance from the model is used for recognizing the words. The wireless communication is carried out by modules RFM 01/02 whose properties fully conform to the assignment. The practical realization of the network which is capable of switching on and off is described in this work. The network is designed to match the requirements of the task and to be economical.

This diploma thesis deals with problems of development of chatbots. The theoretical part of the thesis introduces the concept of the conversational interface in general and analyzes available technologies for its development. The practical part deals with the design and implementation of a particular chatbot, whose goal is to be a virtual assistant in the process of selecting and purchasing goods. This is accomplished by connecting the chatbot to the product information management system using OData web services. One of the biggest problems was to determine the order of questions asked about product properties. For the implementation was used decision tree theory.

The goal of the thesis is being familiar with methods a techniques used in speech processing. Describe the current state of research and development of speech technology. Project and implement server speech recognizer that uses BSAPI. Integrate client that will use server for speech recognition to mobile dictionaries of Lingea company.

Voice comparison is one of the most frequently addressed terms in the context of forensic phonetics; however, so far experts have not been able to find a speech parameter which reliably discriminates between two speakers. Formant dynamics have brought promising results in this respect, therefore in our study using linear discriminant analysis (LDA) we tested the speaker-discriminatory potential of formant trajectories on real forensic recordings. The aim was firstly, to compare the results of LDA when formant frequencies or coefficients of quadratic and cubic fit are used as predictors and secondly, to compare the results when the analyzed classes are balanced or not regarding the number of objects. As for the predictors, all of the types demonstrated comparable classification rates, nevertheless, as LDA limits the number of predictors in relation to the class size, the quadratic fit appears to be the most efficient. Even though LDA was able to discriminate between different voices above chance, it cannot be recommended for forensic use. It delivered highly inconsistent results when the number of objects in the classes was changed; and more importantly, it significantly discriminates between objects of the same speaker. Key words: formant trajectories, voice comparison, LDA, Czech, forensic phonetics