Vowel-reduction feedback system for non-native learners of English

In spoken English, vowels in non-stressed syllables are often reduced to a brief neutral vowel (e.g, e or ι). Non-native speakers of English may not use this `vowel reduction' correctly, so their utterances may sound unnatural. We propose an automatic system to provide feedback about vowel-reduction to non-native speakers of English. The system has three parts: it predicts vowel reduction, detects vowel reduction in speech, compares the prediction to the detected sound to generate a score then uses this score to provide corrective feedback to the speaker. The system had good accuracy and provided positive learning results for the user. The proposed system can be used as a part of a computer-assisted language learning system.

[1]  Anne Cutler,et al.  Stress and accent in language production and understanding , 1984 .

[2]  Luigi Burzio.  Phonology and phonetics of English stress and vowel reduction , 2007 .

[3]  William D. Raymond,et al.  Probabilistic Relations between Words: Evidence from Reduction in Lexical Production , 2008 .

[4]  Eric Fosler-Lussier.  CONTEXTUAL WORD AND SYLLABLE PRONUNCIATION MODELS , 1999 .

[5]  K. Koehler,et al.  The Relationship Between Native Speaker Judgments of Nonnative Pronunciation and Deviance in Segmentais, Prosody, and Syllable Structure , 1992 .

[6]  D. Gibbon,et al.  Intonation, accent, and rhythm : studies in discourse phonology , 1984 .

[7]  Gary Geunbae Lee,et al.  An automatic feedback system for English speaking integrating pronunciation and prosody assessments , 2013, SLaTE.

[8]  Wonyong Sung,et al.  A handheld English pronunciation evaluation device , 2005, 2005 Digest of Technical Papers. International Conference on Consumer Electronics, 2005. ICCE..

[9]  Linda Shockey,et al.  Sound Patterns of Spoken English , 2003 .

[10]  Sungjin Lee,et al.  Grammatical error simulation for computer-assisted language learning , 2011, Knowl. Based Syst..

[11]  GERARD J. DOCHERTY.  Papers in Laboratory Phonology II Gesture , Segment , Prosody , 2011 .

[12]  Yang Liu,et al.  Automatic prosodic events detection using syllable-based acoustic and syntactic features , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Zhizheng Wu,et al.  Automatic prosody prediction and detection with Conditional Random Field (CRF) models , 2010, 2010 7th International Symposium on Chinese Spoken Language Processing.

[14]  Kent L. Norman,et al.  Development of an instrument measuring user satisfaction of the human-computer interface , 1988, CHI '88.

[15]  Ashish Verma,et al.  Sensei: Spoken language assessment for call center agents , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

[16]  A. Cutler,et al.  Rhythmic cues to speech segmentation: Evidence from juncture misperception , 1992 .

[17]  Tatsuya Kawahara,et al.  Practical Use of Autonomous English Pronunciation Learning System for Japanese Students , 2004 .

[18]  Louis Goldstein,et al.  Gesture, Segment, Prosody: “Targetless” schwa: an articulatory analysis , 1992 .

[19]  Shrikanth S. Narayanan,et al.  Exploiting Acoustic and Syntactic Features for Automatic Prosody Labeling in a Maximum Entropy Framework , 2008, IEEE Transactions on Audio, Speech, and Language Processing.