Improved Cocktail - Party Processing

نویسندگان

  • Alexis Favrot
  • Markus Erne
  • Christof Faller
چکیده

The human auditory system is able to focus on one speech signal and ignore other speech signals in an auditory scene where several conversations are taking place. This ability of the human auditory system is referred to as the “cocktail-party effect”. This property of human hearing is partly made possible by binaural listening. Interaural time differences (ITDs) and interaural level differences (ILDs) between the ear input signals are the two most important binaural cues for localization of sound sources, i.e. the estimation of source azimuth angles. This paper proposes an implementation of a cocktail-party processor. The proposed cocktail-party processor carries out an auditory scene analysis by estimating the binaural cues corresponding to the directions of the sources. And next, as a function of these cues, suppresses components of signals arriving from non-desired directions, by speech enhancement techniques. The performance of the proposed algorithm is assessed in terms of directionality and speech quality. The proposed algorithm improves existing cocktail-party processors since it combines low computational complexity and efficient source separation. Moreover the advantage of this cocktailparty processor over conventional beam forming is that it enables a highly directional beam over a wide frequency range by using only two microphones.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Biologically Motivated Solution to the Cocktail Party Problem

We present a new approach to the cocktail party problem that uses a cortronic artificial neural network architecture (Hecht-Nielsen, 1998) as the front end of a speech processing system. Our approach is novel in three important respects. First, our method assumes and exploits detailed knowledge of the signals we wish to attend to in the cocktail party environment. Second, our goal is to provide...

متن کامل

Deep Transform: Cocktail Party Source Separation via Probabilistic Re-Synthesis

In cocktail party listening scenarios, the human brain is able to separate competing speech signals. However, the signal processing implemented by the brain to perform cocktail party listening is not well understood. Here, we trained two separate convolutive autoencoder deep neural networks (DNN) to separate monaural and binaural mixtures of two concurrent speech streams. We then used these DNN...

متن کامل

Measured Performance for Real-Time Localization of Cocktail-Party Talkers

Technology improvements, hardware, software and algorithmic, have made the use of a largeaperture microphone array cost effective. In this paper we present real, measured results for our wired, 128microphone array that surrounds a focal area (room) of about 7Mx5M. While it was necessary to evaluate the performance of the array offline using the array’s recording feature, we ensured that all the...

متن کامل

L'amorçage sémantique masqué en situation de cocktail party (Masked semantic priming in cocktail party situation) [in French]

________________________________________________________________________________________________________ Masked semantic priming in cocktail party situation The present study aimed at testing automatic semantic processing in the auditory modality using the cocktail party situation. Participants had to perform a lexical decision task on a target item embedded in a multi-talker babble. This babbl...

متن کامل

Binaural Scene Analysis and Automatic Speech Recognition

The human auditory system is known to be able to easily analyze and decompose complex acoustic scenes into its constituent acoustic sources. This requires the integration of a multitude of acoustic cues, a phenomenon that is often referred to as cocktail-party processing. Auditory Scene Analysis, especially the segregation and comprehension of concurrent speakers, is one of the key features in ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006