NalyticsNatural Speech and Text Analytics

  1. Ander González-Docasal
  2. Naiara Pérez
  3. Aitor Álvarez
  4. Manex Serras
  5. Laura García Sardiñas
  6. Haritz Arzelus
  7. Aitor García Pablos
  8. Montserrat Cuadros Oller
  9. Paz Delgado
  10. Ane Lazpiur
  11. Blanca Romero
Revue:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Année de publication: 2020

Número: 65

Pages: 119-122

Type: Article

DIALNET GOOGLE SCHOLAR lock_openRUA editor

D'autres publications dans: Procesamiento del lenguaje natural

Résumé

Call centres have long demanded technology for analysing the data they manage. In this context, we present Nalytics, a platform that integrates Speech and Text Analytics in Spanish in a modular design, and capable of customising its models to the users' demands.

Références bibliographiques

  • Amodei, D., S. Ananthanarayanan, R. Anubhai, et al. 2016. Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. In Proceedings of ICML 2016, volume 48, pages 173–182.
  • Bernath, C., A. Alvarez, H. Arzelus, and C. D. Martínez. 2018. Exploring E2E speech recognition systems for new languages. In Proceedings of IberSPEECH 2018, pages 102–106.
  • del Pozo, A., C. Aliprandi, A. Alvarez, et al. 2014. Savas: Collecting, annotating and sharing audiovisual language resources for automatic subtitling. In Proceedings of LREC 2014, pages 432–436.
  • Heafield, K. 2011. Kenlm: Faster and smaller language model queries. In Proceedings of WMT 2011, pages 187–197.
  • Koehn, P., H. Hoang, A. Birch, et al. 2007. Moses: Open source toolkit for statistical machine translation. In Proceedings of the 45th annual meeting of the ACL, pages 177–180.
  • Povey, D., A. Ghoshal, G. Boulianne, et al. 2011. The Kaldi Speech Recognition
  • Toolkit. In Proceedings of ASRU 2011. Tilk, O. and T. Alum¨ae. 2016. Bidirectional Recurrent Neural Network with Attention Mechanism for Punctuation Restoration. In Proceedings of INTERSPEECH 2016.
La source de données: Dialnet