The Cocktail Party Effect Presented by Group 8 廖朝弘 梅衍儂 張雅婷 陳瑋鈴 張筠淇 郭裕芯 組長：劉芳潔 翁怡欣

1.The Inventor 2.Definition 3.Cause 4.Auditory System 5.Recognition of Speech With One and Two Ears 6.Source Separation 7.Automatically Recognizing Streams 8.Conclusion and Games The Cocktail Party Effect

The Inventor of The Cocktail Effect Colin Cherry 1953 Air traffic controllers 1950's

About The Experiment Separate two sounds from a single loudspeaker at the same time gender, direction, speed, pitch

Broadbent’s Filter Theory Our mind can be conceived as a radio receiving many channels at once Which channel we should pay attention ?

The Cocktail Party Effect The ability to focus one's listening attention on a single talker among a mixture of conversations and background noises, ignoring other conversations.

When Does The Cocktail Party Phenomenon Occur? 1.When we are paying attention to one of the sounds around us. 2.When it is invoked by a stimulus which grabs our attention suddenly. three times louder than the ambient noise.

Cause There is a filter in our brain which can select which message we should pay attention to. Ex. If someone call your name in the other side of the party room calls out your name, we can notice that sound and response it immediately. Cause

Outer ear, Middle ear, Inner ear Two ears can identified the location of the sound limit: 20 Hz to 15kHz.distinquish less than 1.5 Hz The auditory system filters sounds received, ignores background noise and concentrate on important information Ex. mothers to the cries of her baby. The ear can differentiate quite subtle sound changes and familiar sounds. Auditory System The Sensory System For The Sense of Hearing

Recognition of Speech With One and Two Ears Different directions Lip-reading, gestures, and the like Different speaking voices Different accents Transition probabilities

No difficulty in listening to one ear A slight delay Temporary memory Recognition of Speech With One and Two Ears

Source Separation Source separation problems in digital signal processing are those in which several signals have been mixed together and the objective is to find out what the original signal were. Principal Components Analysis (PCA) Independent Components Analysis (ICA)

Automatically Recognizing Streams It is generally difficult to find tractable and accurate computational solutions to recognition problems than human find simple. Evidence-partition process Experiment in 1971