NEED SUGGESTIONS ! What Phd direction should I choose that is most relevant to music application in AI?

[hrwa...@gmail.com]

Hey there! 

I am a newbie, and I am going to start my first graduate year in Applied Statistics this September. And I plan to apply for Phd in AI the next year.

My dream is to apply AI in music in the future since I am so fond of both. However, there are a few schools that have Phd direction of AI application in music. So I wish to go to the direction that can be more relevant like NLP, which also uses RNN as basic foundation. 

But since I am not so familiar with this field, can anybody helps me with some suggestion about directions to choose?  

Sorry about my poor English. And thank you for taking time to read my quest!

[Luca Casini]

I applied for a PhD on Machine Learning and Deep Learning in general and got in with a project on generative models applied to music and creative application. I'm starting in november. If I were you I'd try to apply to PhD programmes that have more general scope beside those that are focused on music.

Luca Casini

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[Sharath chandra]

I agree with Luca. If you are interested in music, perhaps you may also be interested in the allied field of listening and auditory perception models.

Speech processing/synthesis and language generation/ translation systems  is a subset of that, but a lot of work in that field is done in corporations

(including Google) and a lot has already been done. Research done in this field that has outputs that see the light of the day are few and far-inbetween in universities, although neuroscience research in language/speech perception has funding and many theoretical highs right now.

 

In listening and auditory perception there is a lot of new research being done, in niche departments, in places like Renselaer Polytechnic (also home to the Deep Listening institute with specialism in Music), Vanderbilt, Rutgers, McGill, Brown, UT Dallas (Callier Center for Hearing & Communication Disorders), etc. The playing field also includes a lot of new research in algorithms for hearing aids as well as adaptive sound in emerging acoustic technologies that doesn't feel like re-inventing the wheel, that use AI/Deep Learning.

Also a lot in the applied science of listening, like the Cornell Bird lab of acoustic ecology, and other sciences where auditory signals are archived to better understand the natural sciences.

In the classic places that do great music, even in CCRMA, CNMAT, the experts involved are not so convinced by the application,excitement, efficacy and human disengagement of AI in music generation. And so it is often difficult to find expert guidance or interest amongst colleagues (they often use and code high quality sound sysnthesis applications using software) Computer musicians like more performative interfaces and leave it too makers of tools like Ableton/Logic/Max(Cyclng74) to include new features. So again, a job in those companies is better that diving into this field as a  PhD.

Goldsmiths University of London, Queen Mary University, are others that do encourage new AI and music making, but again in these place expert musicians with transdisciplinary knowledge and interest may be missing.

Regards

Sharath Chandra Ram

On Thu, Aug 2, 2018 at 4:00 PM, Luca Casini <lucacasin...@gmail.com> wrote:

I applied for a PhD on Machine Learning and Deep Learning in general and got in with a project on generative models applied to music and creative application. I'm starting in november. If I were you I'd try to apply to PhD programmes that have more general scope beside those that are focused on music.

Luca Casini

Il giorno mer 1 ago 2018 alle ore 16:25 <hrwa...@gmail.com> ha scritto:

Hey there! 

I am a newbie, and I am going to start my first graduate year in Applied Statistics this September. And I plan to apply for Phd in AI the next year.

My dream is to apply AI in music in the future since I am so fond of both. However, there are a few schools that have Phd direction of AI application in music. So I wish to go to the direction that can be more relevant like NLP, which also uses RNN as basic foundation. 

But since I am not so familiar with this field, can anybody helps me with some suggestion about directions to choose?  

Sorry about my poor English. And thank you for taking time to read my quest!

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[Hongrui Wang]

Thanks a lot for your suggestion! That helps a lot to me!!!

So I decide to apply for a more general one.  Then I plan to contact a director on NLP direction, and try some projects like language generation during my next two graduate years to be more familiar with deep learning.

And also, I wish to try to do some research on music generation at the meantime. Sometimes I may come up with new ideas for music creation with deep learning, but I really don't know how to start the first step. There's hardly a survey on music generation. 

So could you please tell me some papers or resources for beginners like me? Sorry to bother you. But really thanks a loooooot!!!

And congratulations to your brilliant PHD project! I wish two years later I could be like you ~

在 2018年8月3日星期五 UTC+8上午5:01:09，Luca Casini写道：

[Hongrui Wang]

Thank you so much for your explicit explanation !!!

I were trying to figure out which fields were related to music generation, but little useful information did I collect.  Thanks again for your suggestion! Without your reply, I may never know the next step into which I should go.

I searched and thought about the fields of your suggestion, then decided that the language generation and speech synthesis are both interest me most!

So I decide to find project in these direction, and apply the knowledge to music generation by the meantime.

And I think your suggestion for corporation is great! So in my next graduation years, I will try intern first,then consider if it's necessary to continue research in phd.

Thanks again!!!

Hongrui Wang

在 2018年8月3日星期五 UTC+8上午5:40:53，Sharath Chandra Ram写道：

I agree with Luca. If you are interested in music, perhaps you may also be interested in the allied field of listening and auditory perception models.

Speech processing/synthesis and language generation/ translation systems  is a subset of that, but a lot of work in that field is done in corporations

(including Google) and a lot has already been done. Research done in this field that has outputs that see the light of the day are few and far-inbetween in universities, although neuroscience research in language/speech perception has funding and many theoretical highs right now.

 

In listening and auditory perception there is a lot of new research being done, in niche departments, in places like Renselaer Polytechnic (also home to the Deep Listening institute with specialism in Music), Vanderbilt, Rutgers, McGill, Brown, UT Dallas (Callier Center for Hearing & Communication Disorders), etc. The playing field also includes a lot of new research in algorithms for hearing aids as well as adaptive sound in emerging acoustic technologies that doesn't feel like re-inventing the wheel, that use AI/Deep Learning.

Also a lot in the applied science of listening, like the Cornell Bird lab of acoustic ecology, and other sciences where auditory signals are archived to better understand the natural sciences.

In the classic places that do great music, even in CCRMA, CNMAT, the experts involved are not so convinced by the application,excitement, efficacy and human disengagement of AI in music generation. And so it is often difficult to find expert guidance or interest amongst colleagues (they often use and code high quality sound sysnthesis applications using software) Computer musicians like more performative interfaces and leave it too makers of tools like Ableton/Logic/Max(Cyclng74) to include new features. So again, a job in those companies is better that diving into this field as a  PhD.

Goldsmiths University of London, Queen Mary University, are others that do encourage new AI and music making, but again in these place expert musicians with transdisciplinary knowledge and interest may be missing.

Regards

Sharath Chandra Ram

On Thu, Aug 2, 2018 at 4:00 PM, Luca Casini <lucacasin...@gmail.com> wrote:

I applied for a PhD on Machine Learning and Deep Learning in general and got in with a project on generative models applied to music and creative application. I'm starting in november. If I were you I'd try to apply to PhD programmes that have more general scope beside those that are focused on music.

Luca Casini

Il giorno mer 1 ago 2018 alle ore 16:25 <hrwa...@gmail.com> ha scritto:

Hey there! 

I am a newbie, and I am going to start my first graduate year in Applied Statistics this September. And I plan to apply for Phd in AI the next year.

My dream is to apply AI in music in the future since I am so fond of both. However, there are a few schools that have Phd direction of AI application in music. So I wish to go to the direction that can be more relevant like NLP, which also uses RNN as basic foundation. 

But since I am not so familiar with this field, can anybody helps me with some suggestion about directions to choose?  

Sorry about my poor English. And thank you for taking time to read my quest!

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[Sumit Jetwal]

Hi Everyone ,I am junior at IIIT,UNA.Can Somebody Tell me how to apply for ML intern for Outside From India.

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