15 research outputs found

    Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks

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    Zazo R, Lozano-Diez A, Gonzalez-Dominguez J, T. Toledano D, Gonzalez-Rodriguez J (2016) Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks. PLoS ONE 11(1): e0146917. doi:10.1371/journal.pone.0146917Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (similar to 3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.This work has been supported by project CMC-V2: Caracterizacion, Modelado y Compensacion de Variabilidad en la Señal de Voz (TEC2012-37585-C02-01), funded by Ministerio de Economia y Competitividad, Spain

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    Not AvailablePlant beneficial rhizobacteria (PBR) is a group of naturally occurring rhizospheric microbes that enhance nutrient availability and induce biotic and abiotic stress tolerance through a wide array of mechanisms to enhance agricultural sustainability. Application of PBR has the potential to reduce worldwide requirement of agricultural chemicals and improve agro-ecological sustainability. The PBR exert their beneficial effects in three major ways; (1) fix atmospheric nitrogen and synthesize specific compounds to promote plant growth, (2) solubilize essential mineral nutrients in soils for plant uptake, and (3) produce antimicrobial substances and induce systemic resistance in host plants to protect them from biotic and abiotic stresses. Application of PBR as suitable inoculants appears to be a viable alternative technology to synthetic fertilizers and pesticides. Furthermore, PBR enhance nutrient and water use efficiency, influence dynamics of mineral recycling, and tolerance of plants to other environmental stresses by improving health of soils. This report provides comprehensive reviews and discusses beneficial effects of PBR on plant and soil health. Considering their multitude of functions to improve plant and soil health, we propose to call the plant growth-promoting bacteria (PGPR) as PBR.Not Availabl
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