Language identification for proper name pronunciation
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Summary
This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties like E-modulus and compressive strength.
- Type
- dissertation
- Published
- 2016-01-01
- Cited by
- 2
- References
- 163
- Access
- Open access
- OpenAlex
- https://openalex.org/W2742729777
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:64509332
Keywords
Pronunciation, Identification (biology), Linguistics, Computer science, Natural language processing
References
- Consistency of cross-lingual pronunciation of South African personal names
- Category-based phoneme-to-grapheme transliteration
- A user's guide to support vector machines.
- Improving Pronunciation Accuracy of Proper Names with Language Origin Classes
- On the Naive Bayes Model for Text Categorization
- Text classification and segmentation using minimum cross-entropy
- Language Identification of Short Text Segments with N-gram Models
- Linguistic Techniques to Improve the Performance of Automatic Text Categorization
- Hidden Markov models for grapheme to phoneme conversion
- Language identification of names with SVMs
- Pronunciation modelling of foreign words for Sepedi ASR
- Synthesis of names by a demisyllable-based speech synthesizer (SPOKESMAN)
- G2p variant prediction techniques for ASR and STD
- Learning Rules that Classify E-Mail
- Determining the Origin and Structure of Person Names
- The NCHLT speech corpus of the South African languages
- Natural Language Identification using Corpus-Based Models
- Knowledge of language origin improves pronunciation accuracy of proper names
- Managing Gigabytes: Compressing and Indexing Documents and Images
- Multilingual pronunciations of proper names in a Southern African corpus
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