Publication Details

Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings

YANG Jinyi, ONDEL Yang Lucas Antoine Francois, MANOHAR Vimal and HEŘMANSKÝ Hynek. Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings. In: Proceedings of ICASSP. Brighton: IEEE Signal Processing Society, 2019, pp. 3747-3751. ISBN 978-1-5386-4658-8. Available from: https://ieeexplore.ieee.org/document/8683722
Czech title
K automatickým metodám pro detekci chyb přepisů nahrávek řeči
Type
conference paper
Language
english
Authors
Yang Jinyi (JHU)
Ondel Yang Lucas Antoine Francois, Mgr., Ph.D. (DCGM FIT BUT)
Manohar Vimal (JHU)
Heřmanský Hynek, prof. Ing., Dr.Eng. (JHU)
URL
Keywords

Transcription error detection, model selection, HMM-GMM, Variational Auto-Encoder, detection error tradeoff

Abstract

This work explores different methods to detect errors in transcriptions of speech recordings. We artificially corrupt well transcribed speech transcriptions with three types of errors: substitution, insertion and deletion on TIMIT phonemic transcriptions and WSJ word transcriptions. First, we use Bayesian model selection method by comparing the log-likelihoods from alignment and phone recognizer, a final score is computed to make decision. In this method, we consider two models, Bayesian Hidden Markov Model (HMM) and a Variational Auto-Encoder (VAE) combined with a HMM. Alternately, we build a biased ASR system with language models trained on individual transcriptions, detection decision is based on Levenshtein distance (LD) between transcription and oracle path from decoded lattice. We evaluate the methods of detecting errors in corrupted TIMIT transcription, the best result (either using model selection with VAE model or biased ASR) achieves 7% equal error rate on the Detection Error Tradeoff (DET) curve; we also evaluate the methods of detecting errors in corrupted WSJ transcriptions, and the best result (using biased ASR) achieves 3% equal error rate.

Published
2019
Pages
3747-3751
Proceedings
Proceedings of ICASSP
Conference
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), Brighton, GB
ISBN
978-1-5386-4658-8
Publisher
IEEE Signal Processing Society
Place
Brighton, GB
DOI
UT WoS
000482554003194
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12099,
   author = "Jinyi Yang and Francois Antoine Lucas Yang Ondel and Vimal Manohar and Hynek He\v{r}mansk\'{y}",
   title = "Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings",
   pages = "3747--3751",
   booktitle = "Proceedings of ICASSP",
   year = 2019,
   location = "Brighton, GB",
   publisher = "IEEE Signal Processing Society",
   ISBN = "978-1-5386-4658-8",
   doi = "10.1109/ICASSP.2019.8683722",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12099"
}
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