53 безплатни аудиофайлове за "Mtg"

This is one of the many sounds that reactable from mtg (upf) can do. Mtg is a research group specialized in audio signal processing, music information retrieval, music interfaces, and computational musicology. This sound tries to reflect the work that is being done there about music and computation. Learn more at: https://www. Upf. Edu/web/mtg. Sound taken from reactable demo: https://www. Youtube. Com/watch?v=mgy1s8qymx0.

Male whisper saying: 'welcome to the mtg'.

This is the sound produced when a researcher from mtg is putting their headphones on. Headphones are one of the most used objects at the mtg labs. Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is the sounds that produces an adaptable chair commonly used at mtg when it is moved. It represents a common sounds in the mtg soundscape. Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is a sound of marker writing in a blackboard at mtg (upf). Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is a sound of one of a keyboard which is used at mtg (upf). Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is a sound of one of the gpu’s that are used at mtg (upf). Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is a sound of one of a computer mouse which is used at mtg (upf). Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

This is a sound of a cable jack being connected and disconnected from an input at mtg (upf). Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. Learn more at: https://www. Upf. Edu/web/mtg.

Transformer.

This is a very common sound at mtg (upf), specially at the audio signal processing lab, where they work with world music and computation. Mtg is a research group specialised in audio signal processing, music information retrieval, music interfaces, and computational musicology. This sound tries to reflect the work that is being done there about world music and computation. Learn more at: https://www. Upf. Edu/web/mtg.

This is a short fragment of one of the experiments done by the music and machine learning lab at mtg (upf). The aim is to develop an automatic violin teacher using ml techniques. Mtg is a research group specialized in audio signal processing, music information retrieval, music interfaces, and computational musicology. This sound tries to reflect the work that is being done there about world music and computation. Learn more at: https://www. Upf. Edu/web/mtg. Sound kindly provided by music and machine learning lab from music technology group.

Custom audio for the assignment 7 of aspma course at upf.

Creative audio application of the harmonic plus stochastic transformations module of the sms-tools by the mtg.

Short violin monophonic phrase recorded at home with an iphonex, converted to mono 16bit. Note sequence: b3, c#4, a3, f#4, d4, c#4, ?, a3.

Short violin monophonic phrase recorded with an iphone x and converted to 16bit and mono. Notes come as follow:b3, c#4, a3, f#4, d4, c#4, ?, a3, ?.

Original can be found here: https://freesound. Org/people/xserra/sounds/317745/i applied frequency and time transformations in order to change the intonation and add some dramatism. The transformations i used are from sms-tools (https://github. Com/mtg/sms-tools).

This a piece of the violin a5 sound fromhttps://freesound. Org/people/mtg/sounds/356003/it is under 1 second, converted to sample rate 44100, to be used in thecoursera course "audio signal processing for music applications", given by xavier serra, of universitat pempeu fabra of barcelona.

This a piece of the clarinet a5 sound fromhttps://freesound. Org/people/mtg/sounds/356762/it is under 1 second, converted to sample rate 44100, to be used in thecoursera course "audio signal processing for music applications", given by xavier serra, of universitat pempeu fabra of barcelona.

This a piece of the trumpet a4 sound fromhttps://freesound. Org/people/mtg/sounds/357370/it is under 1 second, converted to sample rate 44100, to be used in thecoursera course "audio signal processing for music applications", given by xavier serra, of universitat pempeu fabra of barcelona.

Analysis of veena concert sound (https://www. Freesound. Org/people/anjds/sounds/377315/ ) with short-time fourier transform model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in the analysis are: - window type = hamming, window size(m) = 1051, fft size (n) = 2048, hop size (h) = 263.

All sounds were downloaded from this site! just practice, thanks for the sounds!these sounds i used have an attribution license, so please give credit to these users:-"trumpet2. Wav" by harbour11 of freesound. Org-"humantrumpet_c. Wav" by pitx of freesound. Org-"trumpet - b major" by mtg of freesound. Org.

Frequency scaled output sound obtained by analysis and synthesis of sound speech-female_hpsmodel. Wav (https://www. Freesound. Org/people/anjds/sounds/377067/) with transformations model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters considered are:-ifrequency scaling factors= [0,1,1,0. 6],ii) frequency stretching factors = [0,1,1,1],iii) timbre preservation = 1, iv) time scaling factors = [0, 0 ,1 ,1].

Frequency scaled output sound obtained by analysis and synthesis of sound speech-female_hpsmodel. Wav (https://www. Freesound. Org/people/anjds/sounds/377067/) with transformations model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters considered are:- i) frequency scaling factors = [0,1. 5,1,0. 6], ii) frequency stretching factors = [0,1,1,1],iii) timbre preservation = 1, iv) time scaling factors = [0, 0 ,1 ,1].

Output sound obtained after frequency scaling and stretching of sound speech-female_hpsmodel. Wav (https://www. Freesound. Org/people/anjds/sounds/377067/) with transformations model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters considered are:- i) frequency scaling factors = [0,1. 5,1,0. 6], ii) frequency stretching factors = [0,1. 5,1,1,2,1. 5],iii) timbre preservation = 1, iv) time scaling factors = [0, 0 ,1 ,1].

The source of this sound is https://freesound. Org/people/doomyd/sounds/530580/ - a clean electric guitar open a string. This sound has been processed using the harmonic plus stochastical analysis of the sms-tools package https://github. Com/mtg/sms-tools with frequency scaling and frequency stretching, to give a metallic flange & 2 octave bend effect.

Output sound obtained after frequency scaling and stretching along with time scaling of sound speech-female_hpsmodel. Wav (https://www. Freesound. Org/people/anjds/sounds/377067/) using transformations model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters considered are:- i) frequency scaling factors = [0,1. 5,1,0. 6], ii) frequency stretching factors = [0,1. 5,1,1,2,1. 5],iii) timbre preservation = 1, iv) time scaling factors = [0, 0 ,1 ,0. 6, 1. 5, 1. 2].

Residual output sound obtained by analysis and synthesis of sound speech-female. Wav (http://freesound. Org/people/xserra/sounds/317745/) with harmonic plus residual model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 2019, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 1, maximum number of harmonics = 100, minimum fundamental frequency = 80, maximum fundamental frequency = 300, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01.

Residual output sound obtained by analysis and synthesis of veena concert sound (https://www. Freesound. Org/people/anjds/sounds/377315/ ) with harmonic plus residual model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 1575, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 01, maximum number of harmonics = 100, minimum fundamental frequency = 100, maximum fundamental frequency = 800, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01.

Resynthesized output obtained from the analysis of a sound of erhu : http://freesound. Org/people/ricemutt/sounds/23933/. This was done using the harmonic plus stochastic model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 1601- fft size: 2048- magnitude threshold: -90- minimum duration of sinusoidal tracks: 0. 1- maximum number of harmonics: 20- minimum fundamental frequency: 100- maximum fundamental frequency: 2000- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 10stochastic approximation factor: 0. 2.

Harmonic sinusoidal output sound obtained by analysis and synthesis of sound speech-female. Wav (http://freesound. Org/people/xserra/sounds/317745/) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 2019, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 1, maximum number of harmonics = 100, minimum fundamental frequency = 80, maximum fundamental frequency = 300, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 7.

Stochastic synthesis output sound obtained by analysis and synthesis of sound speech-female. Wav (http://freesound. Org/people/xserra/sounds/317745/) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 2019, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 1, maximum number of harmonics = 100, minimum fundamental frequency = 80, maximum fundamental frequency = 300, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 7.

Synthesis output sound obtained by analysis and synthesis of sound speech-female. Wav (http://freesound. Org/people/xserra/sounds/317745/) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 2019, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 1, maximum number of harmonics = 100, minimum fundamental frequency = 80, maximum fundamental frequency = 300, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 7.

Stochastic synthesis output sound obtained by analysis and synthesis of veena concert sound (https://www. Freesound. Org/people/anjds/sounds/377315/ ) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 1575, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 01, maximum number of harmonics = 100, minimum fundamental frequency = 100, maximum fundamental frequency = 800, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 2.

Synthesis output sound obtained by analysis and synthesis of veena concert sound (https://www. Freesound. Org/people/anjds/sounds/377315/ ) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 1575, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 01, maximum number of harmonics = 100, minimum fundamental frequency = 100, maximum fundamental frequency = 800, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 2.

Harmonic component obtained from the analysis of a female speech sound: http://www. Freesound. Org/people/xserra/sounds/254374/. This was done using the harmonic plus stochastic model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 2001- fft size: 2048- magnitude threshold: -100- minimum duration of sinusoidal tracks: 0. 05- maximum number of harmonics: 100- minimum fundamental frequency: 150- maximum fundamental frequency: 250- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 0. 05stochastic approximation factor: 1.

Stochastic component obtained from the analysis of a sound of erhu : http://freesound. Org/people/ricemutt/sounds/23933/. This was done using the harmonic plus stochastic model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 1601- fft size: 2048- magnitude threshold: -90- minimum duration of sinusoidal tracks: 0. 1- maximum number of harmonics: 20- minimum fundamental frequency: 100- maximum fundamental frequency: 2000- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 10stochastic approximation factor: 0. 2.

Residual signal obtained after subtracting the harmonics from a female speech sound: http://www. Freesound. Org/people/xserra/sounds/254374/. This was done using the harmonic plus residual model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 2001- fft size: 2048- magnitude threshold: -100- minimum duration of sinusoidal tracks: 0. 05- maximum number of harmonics: 100- minimum fundamental frequency: 150- maximum fundamental frequency: 250- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 0. 02.

Harmonic plus stochastic resynthesis of the female speech sound: http://www. Freesound. Org/people/xserra/sounds/254374/. This was done using the harmonic plus stochastic model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 2001- fft size: 2048- magnitude threshold: -100- minimum duration of sinusoidal tracks: 0. 05- maximum number of harmonics: 100- minimum fundamental frequency: 150- maximum fundamental frequency: 250- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 0. 05stochastic approximation factor: 1.

Harmonic component obtained from the analysis of a sound of erhu : http://freesound. Org/people/ricemutt/sounds/23933/. This was done using the harmonic plus stochastic model implemented in the sms tools: http://mtg. Upf. Edu/technologies/sms. The parameters used for the analysis were:. - window: blackman- window size: 1601- fft size: 2048- magnitude threshold: -90- minimum duration of sinusoidal tracks: 0. 1- maximum number of harmonics: 20- minimum fundamental frequency: 100- maximum fundamental frequency: 2000- maximum error in f0 detection algorithm: 5- max frequency deviation in harmonic tracks: 10stochastic approximation factor: 0. 2.

Harmonic sinusoidal output sound obtained by analysis and synthesis of veena concert sound (https://www. Freesound. Org/people/anjds/sounds/377315/ ) with harmonic plus stochastic model implemented in the sms-tools software package (http://github. Com/mtg/sms-tools)parameters used in analysis are :- window type = blackman, window size(m) = 1575, fft size(n) = 2048, magnitude threshold in db(t) = -100, minimum duration of harmonic tracks = 0. 01, maximum number of harmonics = 100, minimum fundamental frequency = 100, maximum fundamental frequency = 800, maximum error in f0 detection algorithm = 5, max frequency deviation in harmonic tracks = 0. 01,stochastic approximation factor = 0. 2.