Improving the accuracy of pronunciation lexicon using Naive Bayes classifier with character n-gram as feature: for language classified pronunciation lexicon generation
Code (0)
등록된 구현이 없습니다.
Tasks
Language IdentificationSimilar Papers 제목 키워드 기반
Gulf Arabic Linguistic Resource Building for Sentiment Analysis
This paper deals with building linguistic resources for Gulf Arabic, one of the Arabic variations, for sentiment analysis task using machine learning. To our knowledge, no previous works were done for Gulf Arabic sentime…
Arabic Sentiment AnalysisSentiment AnalysisEnsemble of classifiers for speech evaluation
The article describes an attempt to apply an ensemble of binary classifiers to solve the problem of speech assessment in medicine. A dataset was compiled based on quantitative and expert assessments of syllable pronuncia…
ERPLearning Similarity Functions for Pronunciation Variations
A significant source of errors in Automatic Speech Recognition (ASR) systems is due to pronunciation variations which occur in spontaneous and conversational speech. Usually ASR systems use a finite lexicon that provides…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Binary Classificationspeech-recognition+1Twitter Sentiment Analysis: Lexicon Method, Machine Learning Method and Their Combination
This paper covers the two approaches for sentiment analysis: i) lexicon based method; ii) machine learning method. We describe several techniques to implement these approaches and discuss how they can be adopted for sent…
BIG-bench Machine LearningClassificationfeature selectionGeneral Classification+4PronouncUR: An Urdu Pronunciation Lexicon Generator
State-of-the-art speech recognition systems rely heavily on three basic components: an acoustic model, a pronunciation lexicon and a language model. To build these components, a researcher needs linguistic as well as tec…
Grapheme-to-Phoneme ConversionLanguage ModelingLanguage Modellingspeech-recognition+1