ShefCE: A Cantonese-English bilingual speech corpus -- speech recognition model sets and recording transcripts

The Cantonese models include a bigram syllable language model. The English models include a bigram phoneme language model. All model sets are provided in the kaldi format. 1.

The background-cantonese model was trained on CUSENT (68 speakers, 19.4 hours) of read Cantonese speech.2. The background-english model was trained on WSJ-SI84 (83 speakers, 15.2 hours) of read English speech3. The mixed-condition-cantonese model was trained on background-cantonese data and ShefCE Cantonese training data (25 speakers, 9.7 hours).4.

The mixed-condition-english model was trained on background-english data and ShefCE English training data (25 speakers, 2.3 hours) Recording transcripts ----------------------------The recording transcripts are available as a tarball, named, stms.tar.gz, in this repository. These transcripts cover the ShefCE portion of the training data and the ShefCE test data. Four files can be found in the stms.tar.gz archive. - ShefCE_RC.train.v*.stm contains the transcripts for ShefCE training set (Cantonese)- ShefCE_RE.train.v*.stm contains the transcripts for ShefCE training set (English)- ShefCE_RC.test.v*.stm contains the transcripts for ShefCE test set (Cantonese)- ShefCE_RE.test.v*.stm contains the transcripts for ShefCE test set (English) The ShefCE corpus data can be accessed online with DOI:10.15131/shef.data.4522907 Please cite [1] for the use of ShefCE data, models or transcripts.[1] Raymond W. M. Ng, Alvin C.M. Kwan, Tan Lee and Thomas Hain, "ShefCE: A Cantonese-English Bilingual Speech Corpus for Pronunciation Assessment", in Proc.

The 42th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2017.