Presentation Flashcards
Front slide
My name is Gitanjali Sharma and today I will talk about my dissertation project which is called predicting speech-in-noise ability from non-speech stimuli.
Outline
This presentation on my project will cover its background, research aims, methods, main findings, brief discussion and conclusion.
SiN Perception (3)
- During speech-in-noise (SiN) perception, listeners attempt to identify and understand a speaker’s speech among background noise.
- Most of us have been in this situation before, like listening to a friend in a noisy restaurant.
- In order to perceive SiN , the listener must separate target speech from background noise
SiN Difficulty (2)
- It is common for hearing-impaired individuals to have trouble perceiving SiN
- A number of tests to diagnose SiN difficulty has been developed
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SiN Tests
- One of these tests in SiN tests which plays series of speech stimuli (such as words or sentences) against babble noise and asks participants to report the target speech.
- Try to figure out the sentence in your mind as I play an example of SiN tests?
- Did you guess correctly? Here’s is the sentence:
SiN Tests Disadvantage (3)
- The main disadvantage of these SiN tests is that it lacks generalizability to the general population as the speech content is recorded by a native speaker with a specific accent
- There will be an undue performance advantage for participants who speak the same language and accent as the recorded speech content.
- People who don’t might do poorly, resulting in bias in identification of SiN difficulty.
SFG Stimulus (4)
- Stochastic Figure Grounds (SFG) were developed to assess SiN perception.
- You can see on the screen that the SFG stimulus is composed of set of tones with fixed frequency over time (the ‘figure’) against background of tones that are randomized in frequency and time.
- It sounds like this:
- As SFGs have no linguistic content, they can be used by individuals from a wide range of backgrounds and overcome the limitations of SiN tests
Holmes and Griffiths (2)
- Holmes and Griffiths aimed to validate this SFG stimulus as a SiN predictor
- Participants had to say which of two SFG stimuli has a gap in the figure portion in a same-frequency figure discrimination task they created and completed SiN test.
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Holmes and Griffiths Finding (2)
- Results showed that participants’ figure-discrimination task performance significantly correlated with SiN test performance, indicating validity of SFG stimulus
- This relationship was significant, but the correlation value was moderate, which suggests SFG can be improved to stimulate speech more closely
Speech is Harmonic and Dynamic ! (4)
- Taking a closer look at speech, it has two aspects:
- It has a harmonic structure meaning it contains multiples of fundamental frequency
- For example, if a fundamental frequency Is 200 Hz then second harmonic is 400 Hz, third harmonic is 600 Hz etc…
- In addition, speech is dynamic in that frequencies of speech content change over time and we don’t speak with a monotonous voice.
Research Aims (2)
- Figure in SFG stimulus is not dynamic (has fixed frequencies over time) and does not contain harmonic structure which may be needed for it to closer mimic speech better.
- Thus in the study we aimed to create a new version of SFG which figure is dynamic and contains harmoncity, tested its validity in predicting SiN test performance
New Stimulus (1)
Our new stimulus, the harmonic roving SFG (HRSFG) has two versions: on left is low-frequency harmonic auditory figure and on right is high-frequency
Methodology (2)
- This study was conducted in a sound-proof booth with 54 participants recruited via opportunity sampling.
- The participants completed computer tasks that included sentence and word in noise [WiN] test, two versions of pattern discrimination tasks, and a same-frequency figure discrimination task , that used convential SFG, taken from Holmes and Griffiths study.
Pattern Discrimination Task (2)
- A pattern discrimination task involved hearing two examples of the HRSFG stimulus and deciding whether they were the same pattern or different patterns by pressing 1 or 2.
- Separate blocks were ran for the high and low-frequency versions
Main Findings I (2)
- We found that how well the participants were able to detect low and high frequency HRSFG figures were significantly positively correlated with how well they can detect sentences amongst background noise
- HRSFG performances at high and not low frequencies significantly increased explained variance in sentence-in-noise performance compared to conventical SFG performance