vignesh ishwar | Pompeu Fabra University (original) (raw)
Papers by vignesh ishwar
We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large... more We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large collections of Indian art music recordings. The approach first works on single recordings and subsequently searches in the entire music collection. Melodic similarity is based on dynamic time warping. The task being computationally intensive, lower bounding and early abandoning techniques are applied during distance computation. Our dataset comprises 365 hours of music, containing 1,764 audio recordings representing the melodic diversity of Carnatic music. A preliminary evaluation based on expert feedback on a subset of the music collection shows encouraging results. In particular, several musically interesting relationships are discovered, yielding further scope for establishing novel similarity measures based on melodic patterns.Peer reviewe
Proceedings of the SMC Conferences, Sep 14, 2014
Music being an industry with a vast digital presence, today, we have access to a large number of ... more Music being an industry with a vast digital presence, today, we have access to a large number of audio music recordings online as well as stored locally on computers, cell phones, ipads, to name a few devices. Many non-western music cultures have also made a large digital presence over the last two decades. This opens up many windows for applications with state of the art archving, automatic tagging, lyrics to audio alignment and automatic indexing of music using a vast number of cues from the user inputs. It also opens up many avenues for meaningful musical analysis of various music traditions computationally. Melody being one of the most basic entities, predominant pitch is one of the fundamental representations used in all these tasks. In this work we deal with the pitch estimation of the predominant vocal melody from heterophonic music audio recordings. We provide a novel approach for pitch estimation using a combination of the present state of the art and timbral characteristic...
The expression Karn .ā t. ik music is used in common parlance, the correct expression for this is... more The expression Karn .ā t. ik music is used in common parlance, the correct expression for this is Karn .ā t. aka music. Karn .ā t. aka here does not refer to the southern state in India
This work addresses the problem of melodic motif spotting, given a query, in Carnatic music. Melo... more This work addresses the problem of melodic motif spotting, given a query, in Carnatic music. Melody in Carnatic music is based on the concept of raga. Melodic motifs are signature phrases which give a raga its identity. They are also the fundamental units that enable extempore elaborations of a raga. In this paper, an attempt is made to spot typical melodic motifs of a raga queried in a musical piece using a two pass dynamic programming approach, with pitch as the basic feature. In the first pass, the rough longest common subsequence (RLCS) matching is performed between the saddle points of the pitch contours of the reference motif and the musical piece. These saddle points corresponding to quasi-stationary points of the motifs, are relevant entities of the raga. Multiple sequences are identified in this step, not all of which correspond to the the motif that is queried. To reduce the false alarms, in the second pass a fine search using RLCS is performed between the continuous pitch...
Over the last century inKarn. āt .ik 1 music, the method of understandingrāgahas been to break it... more Over the last century inKarn. āt .ik 1 music, the method of understandingrāgahas been to break it down into its various components,vara, scale,gamaka, and phrases. In this paper, an attempt is made to define the abstract concept of rāga in its entirety within the aesthetics of Karn . ̄ t .ik music considering the various components and their symbiotic relationship. This paper also attempts to prove that th e identity of a r̄aga exists as a whole. Section 2 explains the concept of a fundamental musical note or svara. Section 3 illustrates the concept of gamaka or inflections. Section 4 delves into the concept of r āga in detail and then flows into Section 5 which enunciates the identity of a r āga in terms of svara, gamaka, and phraseology. The paper concludes in Section 6, and Section 7 gives the references.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
mining of indian music by extracting arohana-avarohana pattern, " Int.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
Rāga motifs are the main building blocks of the melodic structures in Indian art music. Therefore... more Rāga motifs are the main building blocks of the melodic structures in Indian art music. Therefore, the discovery and characterization of such motifs is fundamental for the computational analysis of this music. We propose an approach for discovering rāga motifs from audio music collections. First, we extract melodic patterns from a collection of 44 hours of audio comprising 160 recordings belonging to 10 rāgas. Next, we characterize these patterns by performing a network analysis, detecting non-overlapping communities, and exploiting the topological properties of the network to determine a similarity threshold. With that, we select a number of motif candidates that are representative of a rāga, the rāga motifs. For a formal evaluation we perform listening tests with 10 professional musicians. The results indicate that, on an average, the selected melodic phrases correspond to rāga motifs with 85% positive ratings. This opens up the possibilities for many musically-meaningful computational tasks in Indian art music, including human-interpretable rāga recognition, semantic-based music discovery, or pedagogical tools.
2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, 2014
Discovery of repeating structures in music is fundamental to its analysis, understanding and inte... more Discovery of repeating structures in music is fundamental to its analysis, understanding and interpretation. We present a data-driven approach for the discovery of shorttime melodic patterns in large collections of Indian art music. The approach first discovers melodic patterns within an audio recording and subsequently searches for their repetitions in the entire music collection. We compute similarity between melodic patterns using dynamic time warping (DTW). Furthermore, we investigate four different variants of the DTW cost function for rank refinement of the obtained results. The music collection used in this study comprises 1,764 audio recordings with a total duration of 365 hours. Over 13 trillion DTW distance computations are done for the entire dataset. Due to the computational complexity of the task, different lower bounding and early abandoning techniques are applied during DTW distance computation. An evaluation based on expert feedback on a subset of the dataset shows that the discovered melodic patterns are musically relevant. Several musically interesting relationships are discovered, yielding further scope for establishing novel similarity measures based on melodic patterns. The discovered melodic patterns can further be used in challenging computational tasks such as automatic rāga recognition, composition identification and music recommendation
Comunicacio presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a I... more Comunicacio presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a Istanbul (Turquia), organitzat per CompMusic.
Journal of New Music Research, 2014
Journal of New Music Research, 2014
Intonation is a fundamental music concept that has a special relevance in Indian art music. It is... more Intonation is a fundamental music concept that has a special relevance in Indian art music. It is characteristic of a rāga and key to the musical expression of the artist. Describing intonation is of importance to several music information retrieval tasks such as developing similarity measures based on rāgas and artists. In this paper, we first assess rāga intonation qualitatively by analyzing varṇaṁs, a particular form of Carnatic music compositions. We then approach the task of automatically obtaining a compact representation of the intonation of a recording from its pitch track. We propose two approaches based on the parametrization of pitch-value distributions: performance pitch histograms, and context-based svara distributions obtained by categorizing pitch contours based on the melodic context. We evaluate both approaches on a large Carnatic music collection and discuss their merits and limitations. We finally go through different kinds of contextual information that can be obtained to further improve the two approaches.
Journal of New Music Research, 2014
e tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist choo... more e tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rāg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rāg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on an average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the laer can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.
Proc. of 2 nd CompMusic Workshop, 2012
In this paper, we describe several techniques for detecting tonic pitch value in Indian classical... more In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This work explores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three ...
We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large... more We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large collections of Indian art music recordings. The approach first works on single recordings and subsequently searches in the entire music collection. Melodic similarity is based on dynamic time warping. The task being computationally intensive, lower bounding and early abandoning techniques are applied during distance computation. Our dataset comprises 365 hours of music, containing 1,764 audio recordings representing the melodic diversity of Carnatic music. A preliminary evaluation based on expert feedback on a subset of the music collection shows encouraging results. In particular, several musically interesting relationships are discovered, yielding further scope for establishing novel similarity measures based on melodic patterns.Peer reviewe
Proceedings of the SMC Conferences, Sep 14, 2014
Music being an industry with a vast digital presence, today, we have access to a large number of ... more Music being an industry with a vast digital presence, today, we have access to a large number of audio music recordings online as well as stored locally on computers, cell phones, ipads, to name a few devices. Many non-western music cultures have also made a large digital presence over the last two decades. This opens up many windows for applications with state of the art archving, automatic tagging, lyrics to audio alignment and automatic indexing of music using a vast number of cues from the user inputs. It also opens up many avenues for meaningful musical analysis of various music traditions computationally. Melody being one of the most basic entities, predominant pitch is one of the fundamental representations used in all these tasks. In this work we deal with the pitch estimation of the predominant vocal melody from heterophonic music audio recordings. We provide a novel approach for pitch estimation using a combination of the present state of the art and timbral characteristic...
The expression Karn .ā t. ik music is used in common parlance, the correct expression for this is... more The expression Karn .ā t. ik music is used in common parlance, the correct expression for this is Karn .ā t. aka music. Karn .ā t. aka here does not refer to the southern state in India
This work addresses the problem of melodic motif spotting, given a query, in Carnatic music. Melo... more This work addresses the problem of melodic motif spotting, given a query, in Carnatic music. Melody in Carnatic music is based on the concept of raga. Melodic motifs are signature phrases which give a raga its identity. They are also the fundamental units that enable extempore elaborations of a raga. In this paper, an attempt is made to spot typical melodic motifs of a raga queried in a musical piece using a two pass dynamic programming approach, with pitch as the basic feature. In the first pass, the rough longest common subsequence (RLCS) matching is performed between the saddle points of the pitch contours of the reference motif and the musical piece. These saddle points corresponding to quasi-stationary points of the motifs, are relevant entities of the raga. Multiple sequences are identified in this step, not all of which correspond to the the motif that is queried. To reduce the false alarms, in the second pass a fine search using RLCS is performed between the continuous pitch...
Over the last century inKarn. āt .ik 1 music, the method of understandingrāgahas been to break it... more Over the last century inKarn. āt .ik 1 music, the method of understandingrāgahas been to break it down into its various components,vara, scale,gamaka, and phrases. In this paper, an attempt is made to define the abstract concept of rāga in its entirety within the aesthetics of Karn . ̄ t .ik music considering the various components and their symbiotic relationship. This paper also attempts to prove that th e identity of a r̄aga exists as a whole. Section 2 explains the concept of a fundamental musical note or svara. Section 3 illustrates the concept of gamaka or inflections. Section 4 delves into the concept of r āga in detail and then flows into Section 5 which enunciates the identity of a r āga in terms of svara, gamaka, and phraseology. The paper concludes in Section 6, and Section 7 gives the references.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
mining of indian music by extracting arohana-avarohana pattern, " Int.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
Rāga motifs are the main building blocks of the melodic structures in Indian art music. Therefore... more Rāga motifs are the main building blocks of the melodic structures in Indian art music. Therefore, the discovery and characterization of such motifs is fundamental for the computational analysis of this music. We propose an approach for discovering rāga motifs from audio music collections. First, we extract melodic patterns from a collection of 44 hours of audio comprising 160 recordings belonging to 10 rāgas. Next, we characterize these patterns by performing a network analysis, detecting non-overlapping communities, and exploiting the topological properties of the network to determine a similarity threshold. With that, we select a number of motif candidates that are representative of a rāga, the rāga motifs. For a formal evaluation we perform listening tests with 10 professional musicians. The results indicate that, on an average, the selected melodic phrases correspond to rāga motifs with 85% positive ratings. This opens up the possibilities for many musically-meaningful computational tasks in Indian art music, including human-interpretable rāga recognition, semantic-based music discovery, or pedagogical tools.
2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, 2014
Discovery of repeating structures in music is fundamental to its analysis, understanding and inte... more Discovery of repeating structures in music is fundamental to its analysis, understanding and interpretation. We present a data-driven approach for the discovery of shorttime melodic patterns in large collections of Indian art music. The approach first discovers melodic patterns within an audio recording and subsequently searches for their repetitions in the entire music collection. We compute similarity between melodic patterns using dynamic time warping (DTW). Furthermore, we investigate four different variants of the DTW cost function for rank refinement of the obtained results. The music collection used in this study comprises 1,764 audio recordings with a total duration of 365 hours. Over 13 trillion DTW distance computations are done for the entire dataset. Due to the computational complexity of the task, different lower bounding and early abandoning techniques are applied during DTW distance computation. An evaluation based on expert feedback on a subset of the dataset shows that the discovered melodic patterns are musically relevant. Several musically interesting relationships are discovered, yielding further scope for establishing novel similarity measures based on melodic patterns. The discovered melodic patterns can further be used in challenging computational tasks such as automatic rāga recognition, composition identification and music recommendation
Comunicacio presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a I... more Comunicacio presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a Istanbul (Turquia), organitzat per CompMusic.
Journal of New Music Research, 2014
Journal of New Music Research, 2014
Intonation is a fundamental music concept that has a special relevance in Indian art music. It is... more Intonation is a fundamental music concept that has a special relevance in Indian art music. It is characteristic of a rāga and key to the musical expression of the artist. Describing intonation is of importance to several music information retrieval tasks such as developing similarity measures based on rāgas and artists. In this paper, we first assess rāga intonation qualitatively by analyzing varṇaṁs, a particular form of Carnatic music compositions. We then approach the task of automatically obtaining a compact representation of the intonation of a recording from its pitch track. We propose two approaches based on the parametrization of pitch-value distributions: performance pitch histograms, and context-based svara distributions obtained by categorizing pitch contours based on the melodic context. We evaluate both approaches on a large Carnatic music collection and discuss their merits and limitations. We finally go through different kinds of contextual information that can be obtained to further improve the two approaches.
Journal of New Music Research, 2014
e tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist choo... more e tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rāg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rāg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on an average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the laer can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.
Proc. of 2 nd CompMusic Workshop, 2012
In this paper, we describe several techniques for detecting tonic pitch value in Indian classical... more In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This work explores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three ...