Projects - User contributions [en]

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:35:10Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

== Introduction ==
=== Project Aims ===

Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.
== Project Team ==

==== Students ====
* Muhammad Haniff Derani
* Shuyang Shen
==== Supervisors ====
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:34:39Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

== Introduction ==
== Project Aims ==

Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.
=== Project Team ===

==== Students ====
* Muhammad Haniff Derani
* Shuyang Shen
==== Supervisors ====
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:34:00Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

== Introduction ==

=== Project Team ===
==== Project Aims ====

Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.

==== Students ====
* Muhammad Haniff Derani
* Shuyang Shen
==== Supervisors ====
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:33:21Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

== Introduction ==

'''Project Team'''
'''Project Aims'''

Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.

'''Students'''
* Muhammad Haniff Derani
* Shuyang Shen
'''Supervisors'''
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:31:12Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

'''Introduction'''

'''Project Team'''
'''Project Aims'''

Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.

'''Students'''
* Muhammad Haniff Derani
* Shuyang Shen
'''Supervisors'''
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:31:02Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).

'''Introduction'''

'''Project Team'''
'''Project Aims'''
Use HARK with PyKALDI on the High-Performance Computer.

Develop an algorithm using HARK for noise processing on HPC.

Evaluate the performance of HARK relative to a number of noise types.

Perform speaker identification using PyKALDI on HPC.

'''Students'''
* Muhammad Haniff Derani
* Shuyang Shen
'''Supervisors'''
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''

Projects:2020s2-7410 Speech Enhancement for Automatic Speech Recognition

2020-09-19T12:30:20Z

A1643070:

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|7410]]

An increasing number of applications require the joint use of signal processing and AI techniques on time series and sensor data. These techniques can be used for the reduction of noises such as air conditioning, computer fan, or environmentally generated noises such as in a street, an airport, in a metro station, or in an airplane cockpit. Developing AI models for signal obtained from a variety of situations as exemplified above is not trivial, but these have been attempted using Recurrent and Convolutional Networks such as Speech Enhanced Generative Adversarial Neural networks (SEGAN).
'''Introduction'''

'''Project Team'''
'''Project Aims'''
Use HARK with PyKALDI on the High-Performance Computer
Develop an algorithm using HARK for noise processing on HPC
Evaluate the performance of HARK relative to a number of noise types
Perform speaker identification using PyKALDI on HPC
'''Students'''
* Muhammad Haniff Derani
* Shuyang Shen
'''Supervisors'''
* Dr. Said Al-Sarawi (
* Dr. Ahmad Hashemi-Sakhtsari (DST Group)

'''Abstract'''