ASR based pronunciation evaluation with automatically generated competing vocabulary
نویسندگان
چکیده
In this paper the application of automatic speech recognition (ASR) technology in CAPT (Computer Aided Pronunciation Training) is addressed. A method to automatically generate the competitive lexicon, required by an ASR engine to compare the pronunciation of a target word with its correct and wrong phonetic realization, is presented. In order to enable the efficient deployment of CAPT applications, the generation of this competitive lexicon does not require any human assistance or a priori information of mother language dependent errors. The method presented here leads to averaged subjective-objective score correlation equal to 0.82 and 0.75 depending on the task.
منابع مشابه
Improved hindi broadcast ASR by adapting the language model and pronunciation model using a priori syntactic and morphophonemic knowledge
In this work, we present a new large-vocabulary, broadcast news ASR system for Hindi. Since Hindi has a largely phonemic orthography, the pronunciation model was automatically generated from text. We experiment with several variants of this model and study the effect of incorporating word boundary information with these models. We also experiment with knowledge-based adaptations to the language...
متن کاملUnsupervised Vocabulary Adaptation for Morph-based Language Models
Modeling of foreign entity names is an important unsolved problem in morpheme-based modeling that is common in morphologically rich languages. In this paper we present an unsupervised vocabulary adaptation method for morph-based speech recognition. Foreign word candidates are detected automatically from in-domain text through the use of letter n-gram perplexity. Over-segmented foreign entity na...
متن کاملMalay Grapheme to Phoneme Tool for Automatic Speech Recognition
This paper presents the design and performance of a Malay grapheme to phoneme (G2P) tool for generating the pronunciation dictionary for a Malay automatic speech recognition system (ASR). The G2P tool is a rule based system. It is flexible in adding and removing rules, and handling of English words. The G2P tool also contains morphological and syllable tool, which it uses to determine the pronu...
متن کاملAnalysis of Dialectal Influence in Pan-Arabic ASR
In this paper, we analyze the impact of five Arabic dialects on the front-end and pronunciation dictionary components of an Automatic Speech Recognition (ASR) system. We use ASR’s phonetic decision tree as a diagnostic tool to compare the robustness of MFCC and MLP front-ends to dialectal variations in the speech data and found that MLP Bottle-Neck features are less robust to such variations. W...
متن کاملData-driven lexical modeling of pronunciation variations for ASR
In this paper a method for the automatic construction of a lexicon with multiple entries per word is described. The basic idea is to transform a reference word transcription by means of stochastic pronunciation rules that can be learned automatically. This approach already proved its potential (Cremelie & Martens, 1999), and is now brought to a much higher level of performance. Relative reducti...
متن کامل