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In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.

Phonetics. --- Speech -- Research. --- Speech processing systems. --- Speech synthesis. --- Speech. --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Electrical Engineering --- Applied Physics --- Telecommunications --- Automatic speech recognition. --- Mechanical speech recognizer --- Speech recognition, Automatic --- Engineering. --- Computational linguistics. --- Phonology. --- Statistics. --- Signal, Image and Speech Processing. --- Language Translation and Linguistics. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Construction --- Industrial arts --- Technology --- Data processing --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pattern recognition systems --- Perceptrons --- Speech, Intelligibility of --- Speech perception --- Speech processing systems --- Natural language processing (Computer science). --- Natural Language Processing (NLP). --- Phonology and Phonetics. --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Grammar, Comparative and general --- Signal processing. --- Image processing. --- Statistics . --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Grammar, Comparative and general Phonology --- Phonology

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.

Statistical science --- Computer. Automation --- Sociolinguistics --- Linguistics --- beeldverwerking --- vertalen --- linguïstiek --- signaalverwerking --- statistisch onderzoek