Hiram Vivanco

ASR based pronunciation evaluation with automatically generated competing vocabulary and classifier fusion

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. Index Terms: second language learning, computer aided pronunciation training, speech recognition and competing vocabulary

Automatic intonation assessment for computer aided language learning

Abstract In this paper the nature and relevance of the information provided by intonation is discussed in the framework of second language learning. As a consequence, an automatic intonation assessment system for second language learning is proposed based on a top-down scheme. A stress assessment system is also presented by combining intonation and energy contour estimation. The utterance pronounced by the student is directly compared with a reference one. The trend similarity of intonation and energy contours are compared frame-by-frame by using DTW alignment. Moreover the robustness of the alignment provided by the DTW algorithm to microphone, speaker and quality pronunciation mismatch is addressed. The intonation assessment system gives an averaged subjective–objective score correlation as high as 0.88. The stress assessment evaluation system gives an EER equal to 21.5%, which in turn is similar to the error observed in phonetic quality evaluation schemes. These results suggest that the proposed systems could be employed in real applications. Finally, the schemes presented here are text- and language-independent due to the fact that the reference utterance text-transcription and language are not required.