<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="singh-biswas-2021-multitask-learning">
    <titleInfo>
        <title>Multitask Learning based Deep Learning Model for Music Artist and Language Recognition</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yeshwant</namePart>
        <namePart type="family">Singh</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Anupam</namePart>
        <namePart type="family">Biswas</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Workshop on Speech and Music Processing 2021</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Anupam</namePart>
            <namePart type="family">Biswas</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rabul</namePart>
            <namePart type="given">Hussain</namePart>
            <namePart type="family">Laskar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Pinki</namePart>
            <namePart type="family">Roy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>NLP Association of India (NLPAI)</publisher>
            <place>
                <placeTerm type="text">NIT Silchar, India</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Artist and music language recognitions of music recordings are crucial tasks in the music information retrieval domain. These tasks have many industrial applications and become much important with the advent of music streaming platforms. This work proposed a multitask learning-based deep learning model that leverages the shared latent representation between these two related tasks. Experimentally, we observe that applying multitask learning over a simple few blocks of a convolutional neural network-based model pays off with improvement in the performance. We conduct experiments on a regional music dataset curated for this task and released for others. Results show improvement up to 8.7 percent in AUC-PR, similar improvements observed in AUC-ROC.</abstract>
    <identifier type="citekey">singh-biswas-2021-multitask-learning</identifier>
    <location>
        <url>https://aclanthology.org/2021.smp-1.3</url>
    </location>
    <part>
        <date>2021-12</date>
        <extent unit="page">
            <start>20</start>
            <end>23</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Multitask Learning based Deep Learning Model for Music Artist and Language Recognition
%A Singh, Yeshwant
%A Biswas, Anupam
%Y Biswas, Anupam
%Y Laskar, Rabul Hussain
%Y Roy, Pinki
%S Proceedings of the Workshop on Speech and Music Processing 2021
%D 2021
%8 December
%I NLP Association of India (NLPAI)
%C NIT Silchar, India
%F singh-biswas-2021-multitask-learning
%X Artist and music language recognitions of music recordings are crucial tasks in the music information retrieval domain. These tasks have many industrial applications and become much important with the advent of music streaming platforms. This work proposed a multitask learning-based deep learning model that leverages the shared latent representation between these two related tasks. Experimentally, we observe that applying multitask learning over a simple few blocks of a convolutional neural network-based model pays off with improvement in the performance. We conduct experiments on a regional music dataset curated for this task and released for others. Results show improvement up to 8.7 percent in AUC-PR, similar improvements observed in AUC-ROC.
%U https://aclanthology.org/2021.smp-1.3
%P 20-23

Markdown (Informal)

[Multitask Learning based Deep Learning Model for Music Artist and Language Recognition](https://aclanthology.org/2021.smp-1.3) (Singh & Biswas, SMP 2021)

• Multitask Learning based Deep Learning Model for Music Artist and Language Recognition (Singh & Biswas, SMP 2021)

ACL

• Yeshwant Singh and Anupam Biswas. 2021. Multitask Learning based Deep Learning Model for Music Artist and Language Recognition. In Proceedings of the Workshop on Speech and Music Processing 2021, pages 20–23, NIT Silchar, India. NLP Association of India (NLPAI).