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Matlab 2018b source code to front- and tail-end zero pad an audio .wav file. In this case relates to the zero-padding applied to the edited and end-pointed individual spoken sentence .wav files of a high-quality digital audio recording of the HARVARD speech corpus in December 2018 at the University of Salford. Adapt this Matlab script to a function by un-muting the first line. Individuals will need to amend the lines regarding the pathways to the input and output files as per their set-up. See also:* EndPoint.m * harvard_201218_British_English_recording.txt* harvard.txt...and the .zip folders containing the audio .wav files
Data Types:
  • Software/Code
A Matlab source code used for end pointing the edited Harvard spoken sentence .wav files a from high-quality digital audio recording generated in December 2018 at the University of Salford. This source code works with the 2018b version of Matlab. Individuals will need to amend the two lines regarding the input/output locations of the .wav file folders as per their own pathways. See the .zip folders for the spoken word .wav files, and the following text files for full details of the recordings:* harvard_201218_British_English_recording.txt* harvard.txt
Data Types:
  • Software/Code
A script compatible with Matlab 2019b to generate speech-shaped noise (SSN) and speech-modulated noise (SMN) using the pwelch method. Includes lines for optional 1/3 octave band smoothing. Requires:* concatenated audio .wav file of 100 spoken sentences* audio .wav file of white noise Amend the lines re: location of input and output files accordingly.
Data Types:
  • Software/Code
A script compatible with Matlab 2019b to generate speech-shaped noise (SSN) and speech-modulated noise (SMN) using the linear predictive coding (LPC) method. Requires:* concatenated audio .wav file of 100 spoken sentences* audio .wav file of white noise Amend the lines re: location of input and output files accordingly. 52nd order recommended for creating SSN and SMN from Demonte (2019): HARVARD speech corpus - audio recording 2019. figshare. collection. (https://doi.org/10.17866/rd.salford.c.4437578.v1)
Data Types:
  • Software/Code
Matlab 2018b source code to front- and tail-end zero pad an audio .wav file. In this case relates to the zero-padding applied to the edited and end-pointed individual spoken sentence .wav files of a high-quality digital audio recording of the HARVARD speech corpus in December 2018 at the University of Salford. Adapt this Matlab script to a function by un-muting the first line. Individuals will need to amend the lines regarding the pathways to the input and output files as per their set-up. See also:* EndPoint.m * harvard_201218_British_English_recording.txt* harvard.txt...and the .zip folders containing the audio .wav files
Data Types:
  • Software/Code
A Matlab source code used for end pointing the edited Harvard spoken sentence .wav files a from high-quality digital audio recording generated in December 2018 at the University of Salford. This source code works with the 2018b version of Matlab. Individuals will need to amend the two lines regarding the input/output locations of the .wav file folders as per their own pathways. See the .zip folders for the spoken word .wav files, and the following text files for full details of the recordings:* harvard_201218_British_English_recording.txt* harvard.txt
Data Types:
  • Software/Code
A script compatible with Matlab 2019b to generate speech-shaped noise (SSN) and speech-modulated noise (SMN) using the pwelch method. Includes lines for optional 1/3 octave band smoothing. Requires:* concatenated audio .wav file of 100 spoken sentences* audio .wav file of white noise Amend the lines re: location of input and output files accordingly.
Data Types:
  • Software/Code
A script compatible with Matlab 2019b to generate speech-shaped noise (SSN) and speech-modulated noise (SMN) using the linear predictive coding (LPC) method. Requires:* concatenated audio .wav file of 100 spoken sentences* audio .wav file of white noise Amend the lines re: location of input and output files accordingly. 52nd order recommended for creating SSN and SMN from Demonte (2019): HARVARD speech corpus - audio recording 2019. figshare. collection. (https://doi.org/10.17866/rd.salford.c.4437578.v1)
Data Types:
  • Software/Code
This is an initial study to characterise rollator movement. An inertial measurement unit (IMU) was used to measure the motion of the rollator and analytical approaches were developed to extract features characterising the rollator movement, properties of the surface, and push events. The analytics were tested in two situations, firstly a healthy participant used a rollator in a laboratory using a motion capture system to obtain ground truth. Secondly the IMU was used to measure the movement of a rollator being used by a user with multiple sclerosis (MS) on a flat surface, cross-slope, up and down slopes, and up and down a step. Unzip the entire folder and run calcDistance.m and it will load the IMU data from the Xsens_rollator folder and then create fig files in the OutputFigs folder. There are also variables in this zip file that contain output data (meanPushDist and totalPushes) which show average push distance and total number of pushes for each trial.
Data Types:
  • Software/Code
This is an initial study to characterise rollator movement. An inertial measurement unit (IMU) was used to measure the motion of the rollator and analytical approaches were developed to extract features characterising the rollator movement, properties of the surface, and push events. The analytics were tested in two situations, firstly a healthy participant used a rollator in a laboratory using a motion capture system to obtain ground truth. Secondly the IMU was used to measure the movement of a rollator being used by a user with multiple sclerosis (MS) on a flat surface, cross-slope, up and down slopes, and up and down a step. Unzip the entire folder and run calcDistance.m and it will load the IMU data from the Xsens_rollator folder and then create fig files in the OutputFigs folder. There are also variables in this zip file that contain output data (meanPushDist and totalPushes) which show average push distance and total number of pushes for each trial.
Data Types:
  • Software/Code