Transparent communication

Transparent communication refers to the audio signal processing which is applied in communication applications The goal is to make the audio as transparent as possible in the sense that the reproduced audio should ideally be free from reverberation noise acoustical echos and mixed speakers Application areas are for example teleconferencing and handsfree telephony This paper presents new ideas for the implementation of such a system In particular the use of blind signal separation is examined and new ideas are presented for the joint implementation of the MultiChannel Acoustical Echo Canceler MC AEC and the Blind Signal Separation BSS In this way acoustical quality can be improved at a reduced computational cost

On the performance of too short adaptive FIR filters

Performance analyses of adaptive algorithms such as LMS and RLS often rely on the assumption that the input signal is stationary. Also it often is assumed that the adaptive nite impulse response FIR filter is long enough to make a good approximation of the unknown system. In many practical situations these assumptions do not hold and the instantaneous misadjustment of the adaptive filter can grow large. In this paper this effect is investigated and two methods are presented to improve the performance of the adaptive filter

Realtime realization aspects of the CoBliSS blind signal separation algorithm

Recently, the Convolutive Blind Signal Separation algorithm (CoBliSS) was introduced. CoBliSS is based on second order statics only and is able to control a multichannel filter with thousands of tabs as is required in acoustical applications. In this paper the feasibility of a real-time implementation of the CoBliSS algorithm is investigated. An efficient implementation is proposed and the corresponding computational complexity is discussed

On the indeterminacies of convolutive blind signal separation based on second-order statistics

Recently, several blind signal separation algorithms have been developed which are based on second order statistics. Little has been published however on whether second order statistics are sufficient to obtain a unique solution. Especially for applications that involve convolutive mixing and unmixing of signals that are correlated in time, there is a lack of knowledge on why and in what cases second order statistics suffice. This paper investigates the indeterminacies that are introduced when second order statistics are used and presents a theorem for the unmixing system to be uniquely found using second order statistics

A new algorithm for joint blind signal separation and acoustic echo canceling

The problem of joint blind signal separation and acoustic echo cancelling arises in applications such as teleconferencing and voice controlled machinery. Microphones pick up a signal of the desired speaker together with contributions of other speakers and loudspeakers in these applications. The contributions of these loudspeaker signals to the microphone signals need to be cancelled. The remaining signals are then separated so that the individual local speakers are recovered. In this paper an extension of the recently introduced Convolutive Blind Signal Separation algorithm; CoBliSS is presented. This extended algorithm is capable of performing combined blind signal separation and acoustical echo cancelling at a low computational cost. The performance of the extended CoBliSS algorithm is evaluated using audio that is recorded in a real acoustical environment

Method for cancelling unwanted loudspeaker signals

In a method for canceling unwanted signals from at least one external sound source, such as a loudspeaker, by means of headphones provided with microphones, at least known sound signals from the at least one external sound source are compensated by anti-phase sound signals. These sound signals simulate the at least known sound signals from said at least one external sound source in anti-phase. Said anti-phase sound signals are generated in the headphones in response to signals derived from audio input signals of the at least one external sound source in a filter device which is controlled by the resulting microphone signals

A new algorithm for joint blind signal separation and acoustic echo canceling

The problem of joint blind signal separation and acoustic echo cancelling arises in applications such as teleconferencing and voice controlled machinery. Microphones pick up a signal of the desired speaker together with contributions of other speakers and loudspeakers in these applications. The contributions of these loudspeaker signals to the microphone signals need to be cancelled. The remaining signals are then separated so that the individual local speakers are recovered. In this paper an extension of the recently introduced Convolutive Blind Signal Separation algorithm; CoBliSS is presented. This extended algorithm is capable of performing combined blind signal separation and acoustical echo cancelling at a low computational cost. The performance of the extended CoBliSS algorithm is evaluated using audio that is recorded in a real acoustical environment