Phoneme Similarity Matrices to Improve Long Audio Alignment for Automatic Subtitling

Pablo Ruiz, Aitor Álvarez, Haritz Arzelus

Abstract
Long audio alignment systems for Spanish and English are presented, within an automatic subtitling application. Language-specific phone decoders automatically recognize audio contents at phoneme level. At the same time, language-dependent grapheme-to-phoneme modules perform a transcription of the script for the audio. A dynamic programming algorithm (Hirschberg’s algorithm) finds matches between the phonemes automatically recognized by the phone decoder and the phonemes in the script’s transcription. Alignment accuracy is evaluated when scoring alignment operations with a baseline binary matrix, and when scoring alignment operations with several continuous-score matrices, based on phoneme similarity as assessed through comparing multivalued phonological features. Alignment accuracy results are reported at phoneme, word and subtitle level. Alignment accuracy when using the continuous scoring matrices based on phonological similarity was clearly higher than when using the baseline binary matrix.
Anthology ID:
L14-1335
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
437–442
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/387_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Pablo Ruiz, Aitor Álvarez, and Haritz Arzelus. 2014. Phoneme Similarity Matrices to Improve Long Audio Alignment for Automatic Subtitling. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 437–442, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Phoneme Similarity Matrices to Improve Long Audio Alignment for Automatic Subtitling (Ruiz et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/387_Paper.pdf
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