In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.

Achieving a low noise level is of great interest to the forest machine industry. Traditionally this is obtained by using passive noise reduction, i.e. by using materials for sound isolation and sound absorption. Especially designs to attenuate low frequency noise tend to be bulky and impractical from an installation point of view. An alternative solution to the problem is to use active noise control (ANC). The basic principle of ANC is to generate an anti-noise signal designed to destructively interfere with the unwanted noise. In this thesis two algorithms (Feedback FxLMS and Feedforward FxLMS) are implemented and evaluated for use in the ANC-system. The ANC-system is tuned to the specific environment in the driver’s cabin of a Komatsu forest machine. The algorithms are first tested in a simulated environment and then in real-time inside a forest machine. Simulations are made both in Matlab and in C using both generated signals and recorded signals. The C code is implemented on the Analog Devices Blackfin DSP card BF526. The result showed a significantly reduction of the sound pressure level (SPL) in the driver’s cabin. The noise attenuation obtained using the Feedback FxLMS was approximately 14 dB for a tonal 100 Hz signal and 11 dB using recorded engine noise from a forest machine at 850 rpm.

<p>In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.</p>

In automatic speech recognition systems (ASRs), training is a critical phase to the system?s success. Communication media, either analog (such as analog landline phones) or digital (VoIP) distort the speaker?s speech signal often in very complex ways: linear distortion occurs in all channels, either in the magnitude or phase spectrum. Non-linear but time-invariant distortion will always appear in all real systems. In digital systems we also have network effects which will produce packet losses and delays and repeated packets. Finally, one cannot really assert what path a signal will take, and so having error or distortion in between is almost a certainty. The channel introduces an acoustical mismatch between the speaker's signal and the trained data in the ASR, which results in poor recognition performance. The approach so far, has been to try to undo the havoc produced by the channels, i.e. compensate for the channel's behavior. In this thesis, we try to characterize the effects of different transmission media and use that as an inexpensive and repeatable way to train ASR systems.