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International Conference on Applications of Natural Language to Information Systems

NLDB 2015: Natural Language Processing and Information Systems pp 249–260Cite as

Tree-Structured Named Entities Extraction from Competing Speech Transcriptions

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9103))

Abstract

When real applications are working with automatic speech transcription, the first source of error does not originate from the incoherence in the analysis of the application but from the noise in the automatic transcriptions. This study presents a simple but effective method to generate a new transcription of better quality by combining utterances from competing transcriptions. We have extended a structured Named Entity (NE) recognizer submitted during the ETAPE Challenge. Working on French TV and Radio programs, our system revises the transcriptions provided by making use of the NEs it has detected. Our results suggest that combining the transcribed utterances which optimize the F-measures, rather than minimizing the WER scores, allows the generation of a better transcription for NE extraction. The results show a small but significant improvement of 0.9 % SER against the baseline system on the ROVER transcription. These are the best performances reported to date on this corpus.

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Notes

  1. 1.

    \(WER=\frac{S+D+I}{N}\), where D, I, S stand for the number of deletions, insertions, substitutions of words and N for the total number of words in the reference.

  2. 2.

    More information about the challenge can be found at www.afcp-parole.org/etape/workshop.html.

  3. 3.

    As a first working hypothesis, we have segmented the transcriptions based on the gold standard utterances.

  4. 4.

    SCLite: www1.icsi.berkeley.edu/Speech/docs/sctk-1.2/sclite.htm.

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Acknowledgments

We thank Dr. Abeed Sarker and Dr. Graciela Gonzalez for their helpful comments and remarks.

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Authors and Affiliations

  1. INSA - IRISA, INRIA de Rennes, 20 Avenue des Buttes de Coësmes, Rennes, France

    Davy Weissenbacher & Christian Raymond

Authors
  1. Davy Weissenbacher
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  2. Christian Raymond
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Corresponding author

Correspondence to Davy Weissenbacher .

Editor information

Editors and Affiliations

  1. Technische Universität Darmstadt, Darmstadt, Germany

    Chris Biemann

  2. Universität Passau, Passau, Germany

    Siegfried Handschuh

  3. Universität Passau, Passau, Germany

    André Freitas

  4. University of Salford, Salford, United Kingdom

    Farid Meziane

  5. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

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Weissenbacher, D., Raymond, C. (2015). Tree-Structured Named Entities Extraction from Competing Speech Transcriptions. In: Biemann, C., Handschuh, S., Freitas, A., Meziane, F., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2015. Lecture Notes in Computer Science(), vol 9103. Springer, Cham. https://doi.org/10.1007/978-3-319-19581-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-19581-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19580-3

  • Online ISBN: 978-3-319-19581-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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