TASK DEFINITION: In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].
PROBLEM: While I understand the difficulty of collecting audio data from animals, I think this type of feature engineering does not go in the right direction. I would rather see a model than learns the feature representation from data.  I would think it should be possible to collect a more substantial corpus in zoos / nature etc, and then train a generative model. The underlying learned feature representation could be then used to feed a classifier. I'm not familiar with the particularities of this task, it's hard to judge the improvements by using chirplets.

SOLUTION: en

PROBLEM: This paper is technically sound. It highlights well the strengths and weaknesses of the proposed simplified model.  In terms of impact, its novelty is limited, in the sense that the authors did seemingly the right thing and obtained the expected outcomes. The idea of modeling deep learning computation is not in itself particularly novel. As a companion paper to an open source release of the model, it would meet my bar of acceptance in the same vein as a paper describing a novel dataset, which might not provide groundbreaking insights, yet be generally useful to the community.  In the absence of released code, even if the authors promise to release it soon, I am more ambivalent, since that's where all the value lies. It would also be a different story if the authors had been able to use this framework to make novel architectural decisions that improved training scalability in some way, and incorporated such new insights in the paper.  UPDATED: code is now available. Revised review accordingly.

SOLUTION: en

PROBLEM: Es un artículo que presenta una diagnóstico interesante de las empresas de desarrollo de software de Chile. Incorporan una base estadística inicial que da formalidad al trabajo realizado, de manera específica para la determinación de la muestra base para el desarrollo de las encuestas. Sin embargo, los datos estadísticos de los resultados no hacen parte del trabajo presentado.  Presentación de resultados estadísticos que validen las conclusiones presentadas y los hallazgos encontrados, acerca del diagnóstico.  Se recomienda a los autores continuar en el trabajo a fin incorporar las bases estadísticas tendiente en las empresas del sector en otros países.  Otras recomendaciones:  Revisión exhaustiva del inglés y de forma particular para la presentación de artículo, debería revisarse de forma cuidadosa la traducción de este idioma. Revisar particularmente el título, donde hay un error en la primera palabra.

SOLUTION:
es