@inproceedings{blandin-etal-2020-age,
    title = "Age Recommendation for Texts",
    author = "Blandin, Alexis  and
      Lecorv{\'e}, Gw{\'e}nol{\'e}  and
      Battistelli, Delphine  and
      {\'E}tienne, Aline",
    editor = "Calzolari, Nicoletta  and
      B{\'e}chet, Fr{\'e}d{\'e}ric  and
      Blache, Philippe  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.lrec-1.179/",
    pages = "1431--1439",
    language = "eng",
    ISBN = "979-10-95546-34-4",
    abstract = "The understanding of a text by a reader or listener is conditioned by the adequacy of the text{'}s characteristics with the person{'}s capacities and knowledge. This adequacy is critical in the case of a child since her/his cognitive and linguistic skills are still under development. Hence, in this paper, we present and study an original natural language processing (NLP) task which consists in predicting the age from which a text can be understood by someone. To do so, this paper first exhibits features derived from the psycholinguistic domain, as well as some coming from related NLP tasks. Then, we propose a set of neural network models and compare them on a dataset of French texts dedicated to young or adult audiences. To circumvent the lack of data, we study the idea to predict ages at the sentence level. The experiments first show that the sentence-based age recommendations can be efficiently merged to predict text-based recommendations. Then, we also demonstrate that the age predictions returned by our best model are better than those provided by psycholinguists. Finally, the paper investigates the impact of the various features used in these results."
}Markdown (Informal)
[Age Recommendation for Texts](https://preview.aclanthology.org/ingest-emnlp/2020.lrec-1.179/) (Blandin et al., LREC 2020)
ACL
- Alexis Blandin, Gwénolé Lecorvé, Delphine Battistelli, and Aline Étienne. 2020. Age Recommendation for Texts. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1431–1439, Marseille, France. European Language Resources Association.