1. Frenchay Dysarthria Assessment: What’s new?
Rebecca Palmer, Pam Enderby, James Carmichael

2. Topics Original FDA overview
Advantages and disadvantages of this assessment
FDA 2 – new aspects
Computerised FDA
Demonstration
Current work on automated intelligibility testing

3. Original FDA Author: Pam Enderby First published in 1983
Result of research identifying nature and patterns of oromotor movements associated with different neurological diseases (Enderby 1983)
Translated into French, German, Dutch, Norwegian, Swedish, Finnish, Catalan and Castilian

4. Aim of FDA
To analyse several important parameters of the motor speech system
To guide treatment
To assist with neurological diagnosis
To have good reliability and validity between and within clinicians without extensive training

5. Structure of FDA Reflexes Respiration Lips Palate Laryngeal Tongue
Cough, swallow, dribble/drool
Respiration
At rest, in speech
Lips
At rest, spread, seal, alternate, in speech
Palate
Fluids, maintenance, in speech
Laryngeal
Time, pitch, volume, in speech
Tongue
At rest, protrusion, elevation, lateral, alternate, in speech
Intelligibility
Words, sentences, conversation

6. Procedure Ask patient to carry out a task
Rate ability of each parameter using a 9 point scale – 5 descriptors + ½ marks

7. Advantages of FDA
Intelligibility commonly used to assess severity of dysarthria and to monitor progress BUT Intelligibility measures alone do not diagnose type of dysarthria or guide treatment
FDA breaks speech up into its component parts so the clinician can analyse what contributes to the reduced intelligibility thus guiding treatment
FDA provides a profile that contributes to the neurological diagnosis

8. Disadvantages of FDA Some measures can be subjective
Some descriptors are interpreted differently by different clinicians reducing reliability
Intelligibility section:
Too few words/sentences regular users can learn them
Sentence structure = ‘the man is…’ therefore only listening for the last word
Scoring system based on number listener understood out of 10 (crude)

9. FDA 2 Authors: Pam Enderby & Rebecca Palmer 2008
Aim: To address theoretical and practical issues identified in reviews of the first edition

10. Improvements 1
Omitted items that have been found to be unreliable or redundant to the purposes of diagnosis and treatment
e.g. Jaw tests – patients rarely have abnormality in the jaw therefore the information didn’t assist diagnosis

11. Improvements 2 Improved reliability of descriptors
Inter-rater reliability testing between experienced users of the FDA showed that some descriptors were interpreted differently.
E.g. voice time
Patient can say ‘ah’ for 15 seconds
Patient unable to sustain clear voice for 3 seconds
Constant hoarse voice – RP = a), PE = e)

12. Improvements 2 Inter rater and test retest reliability
Audio recordings of 9 people with a range of types and severities of dysarthria performing the audible FDA 2 tests:
6 speech therapists working with a mixed adult caseload judged 42 examples of FDA 2 tests.
Scored on a 9 point scale
Same 42 tests presented again to the listeners after 6 week interval
Inter and intra rater reliability were calculated using intra class correlation coefficients

13. Inter and intra judge reliability1 2 3 4 5 6
0.76
0.77
0.92
0.56
0.65
0.72
0.67
0.60
0.51 -
0.38
0.52
0.49
0.79
0.73
0.66
0.70
Criteria for interpretation of reliability coefficients for ordinal measures (Landis & Koch, 1977):
<0 = poor, = slight, = fair,
= moderate (mod), = substantial (sub)
0.81 – 1 = almost perfect (per)

14. Improvements 3 In speech tests
Sound saturated sentences provided for patient to say so that clinician can listen to the accuracy of sound placement in speech
Lips in speech:
‘Mary brought me a piece of maple syrup pie’
Tongue in speech:
‘Kenneth’s dog took ten tiny ducks today’

15. Improvements 4 Intelligibility testing New set of words
Corpus of 116 words to reduce probability of listeners learning the words with increased exposure
Phonetically balanced list for types of sounds, position of sounds in words, word length
Word frequency >10 per million to control for any effects of word frequency on intelligibility

16. Improvements 4 Sentence intelligibility
Key words phonetically balanced to account for place, manner, position and word length
Carrier phrases/sentences are all different so the listener has to listen to a sentence, not just interpret the key word in a standard carrier phrase
‘Can you go the shop?’
‘My daughter is a nurse’
‘Lets go to the theatre’

17. Availability
FDA 2 available now from Pro-ed
Only in English!

18. Computerised FDA James Carmichael produced computer version
Demonstration

19. Planned additions to CFDA Automation of intelligibility testing – modelling the naiive listener
If the learning effect alters a listener’s perception of a particular individual’s speaking style, is that listener’s judgement still representative of the naïve listener?
Can a computer model be built which behaves like an “eternal” naïve listener (i.e. never adapting to an unfamiliar speaking style and therefore always consistent in assessment)?

20. Using HMM Models to Emulate the Naïve listener
A hidden Markov Model (HMM)
a statistical representation of a speech unit at the phone/word/utterance level.
HMM models are “trained” by analysing the acoustic features of multiple utterances representing the specified speech unit.
'Everyman' HMM Word Model
Multiple Speech Samples from multiple speakers

21. Goodness of fit
Once trained, an HMM word model can be used to estimate the likelihood that a given speech sound could have actually been produced by that word model.
This likelihood is called a goodness of fit (GOF)
expressed as a log likelihood, e.g (or simply expressed as -35).

22. Comparing GOF scores with Subjective Assessments
3 important cues of intelligibility are:
hesitation time;
speech rate
a phoneme-by-phoneme comparison of what the speaker intended to say and what the listener actually heard.

23. Calculating Phonetic Convergence
Phoneme comparison of intended and perceived message: “You have to pay”
(for a mildly dysarthric speaker)
Intended
/j/
/u:/
/h/
/æ/
/v/
/t/
/p/
/e/
Heard
/d/
/b/
/aι/
Convergence 1
Word Level Deletion -1
Overall Convergence
5 out of a possible 9 = 0.56 (56%)

24. Phonetic convergence
Hesitation L1 L5
L10
L15
L20
Listeners L1 L5
L10
L20
L15
Listeners
Mild, Moderate, Severe
Mild, Moderate, Severe
Speech rate
Speech rate’s correlation with intelligibility is not as good as hesitation time or phonetic convergence, so we derive a Perceptual Intelligibility Index (PII) based on the Phonetic Convergence score weighted by a hesitation time coefficient
Mild, Moderate, Severe

25. How well do automated GOF scores correlate with Perceptual intelligibility index?
Speaker
Phon. Convergence
Hesitation Time coefficient
Sentence PII Score
Avg. GOF Score
Mild
0.95
0.91
0.86
-34
Moderate
0.27
0.15
0.11
-61
Severe
0.20
0.19
0.04
-85
Correlation between GOF scores and PII scores =0.72
Automated scores of goodness of fit measures generated by HMMs could be a valid and consistent intelligibility measure

26. Summary FDA 2 Analyses each parameter of speech
Enables clinician to find cause of reduced intelligibility, guiding treatment
Assists with diagnosis of dysarthria type and neurological impairment
Excludes redundant tests
Uses non-ambiguous descriptors
Has inter and intra-rater reliability
Large corpus of words and sentences controlled for linguistic and phonetic parameters for intelligibility sections
Word and sentence cards provided

27. Summary Computerised FDA Provides training test for new users
Automatically produces profile and stores information
Increases objectivity of measures
Provides visual feedback of performance and improvements to patient
Seeks to automate measurement of intelligibility leading to increased consistency

28. Thank you !