Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
YANG, J. ONDEL YANG, L. MANOHAR, V. HEŘMANSKÝ, H.
Originální název
Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Transcription error detection, model selection, HMM-GMM, Variational Auto-Encoder, detection error tradeoff
Autoři
YANG, J.; ONDEL YANG, L.; MANOHAR, V.; HEŘMANSKÝ, H.
Vydáno
12. 5. 2019
Nakladatel
IEEE Signal Processing Society
Místo
Brighton
ISBN
978-1-5386-4658-8
Kniha
Proceedings of ICASSP
Strany od
3747
Strany do
3751
Strany počet
5
URL
https://ieeexplore.ieee.org/document/8683722
BibTex
@inproceedings{BUT160007, author="YANG, J. and ONDEL YANG, L. and MANOHAR, V. and HEŘMANSKÝ, H.", title="Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings", booktitle="Proceedings of ICASSP", year="2019", pages="3747--3751", publisher="IEEE Signal Processing Society", address="Brighton", doi="10.1109/ICASSP.2019.8683722", isbn="978-1-5386-4658-8", url="https://ieeexplore.ieee.org/document/8683722" }