Detail publikace

Towards Automatic Methods to Detect Errors in Transcriptions of Speech Recordings

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"
}

Dokumenty

yang_icassp2019_0003747.pdf