List Equivalency of PRESTO for the Evaluation of Speech Recognition.

BACKGROUND There is a pressing clinical need for the development of ecologically valid and robust assessment measures of speech recognition. Perceptually Robust English Sentence Test Open-set (PRESTO) is a new high-variability sentence recognition test that is sensitive to individual differences and was designed for use with several different clinical populations. PRESTO differs from other sentence recognition tests because the target sentences differ in talker, gender, and regional dialect. Increasing interest in using PRESTO as a clinical test of spoken word recognition dictates the need to establish equivalence across test lists. PURPOSE The purpose of this study was to establish list equivalency of PRESTO for clinical use. RESEARCH DESIGN PRESTO sentence lists were presented to three groups of normal-hearing listeners in noise (multitalker babble [MTB] at 0 dB signal-to-noise ratio) or under eight-channel cochlear implant simulation (CI-Sim). STUDY SAMPLE Ninety-one young native speakers of English who were undergraduate students from the Indiana University community participated in this study. DATA COLLECTION AND ANALYSIS Participants completed a sentence recognition task using different PRESTO sentence lists. They listened to sentences presented over headphones and typed in the words they heard on a computer. Keyword scoring was completed offline. Equivalency for sentence lists was determined based on the list intelligibility (mean keyword accuracy for each list compared with all other lists) and listener consistency (the relation between mean keyword accuracy on each list for each listener). RESULTS Based on measures of list equivalency and listener consistency, ten PRESTO lists were found to be equivalent in the MTB condition, nine lists were equivalent in the CI-Sim condition, and six PRESTO lists were equivalent in both conditions. CONCLUSIONS PRESTO is a valuable addition to the clinical toolbox for assessing sentence recognition across different populations. Because the test condition influenced the overall intelligibility of lists, researchers and clinicians should take the presentation conditions into consideration when selecting the best PRESTO lists for their research or clinical protocols.

[1]  D. Pisoni,et al.  Effects of cross-language voice training on speech perception: whose familiar voices are more intelligible? , 2011, The Journal of the Acoustical Society of America.

[2]  W. Noble,et al.  The Speech, Spatial and Qualities of Hearing Scale (SSQ) , 2004, International journal of audiology.

[3]  Brian C J Moore,et al.  STARR: A Speech Test for Evaluation of the Effectiveness of Auditory Prostheses Under Realistic Conditions , 2013, Ear and hearing.

[4]  A. Thornton,et al.  Speech-discrimination scores modeled as a binomial variable. , 1978, Journal of speech and hearing research.

[5]  M. Dorman,et al.  Performance of subjects fit with the Advanced Bionics CII and Nucleus 3G cochlear implant devices. , 2004, Archives of otolaryngology--head & neck surgery.

[6]  D L Neff,et al.  Individual differences in simultaneous masking with random-frequency, multicomponent maskers. , 1995, The Journal of the Acoustical Society of America.

[7]  Thomas Lunner,et al.  When cognition kicks in: working memory and speech understanding in noise. , 2010, Noise & health.

[8]  René H. Gifford,et al.  Evidence for the Expansion of Adult Cochlear Implant Candidacy , 2010, Ear and hearing.

[9]  D. Pisoni,et al.  Effects of stimulus variability on speech perception in listeners with hearing impairment. , 1997, Journal of speech, language, and hearing research : JSLHR.

[10]  Eric W Healy,et al.  The consistency of sentence intelligibility across three types of signal distortion. , 2007, Journal of speech, language, and hearing research : JSLHR.

[11]  Rachel A McArdle,et al.  An Evaluation of the BKB-SIN, HINT, QuickSIN, and WIN Materials on Listeners With Normal Hearing and Listeners With Hearing Loss. , 2007, Journal of speech, language, and hearing research : JSLHR.

[12]  D. Pisoni,et al.  Talker-specific learning in speech perception , 1998, Perception & psychophysics.

[13]  P F Assmann,et al.  Acoustic and linguistic factors in the perception of bandpass-filtered speech. , 2001, The Journal of the Acoustical Society of America.

[14]  Michael F Dorman,et al.  Development and Validation of the AzBio Sentence Lists , 2012, Ear and hearing.

[15]  D. Pisoni,et al.  Recognition of spoken words by native and non-native listeners: talker-, listener-, and item-related factors. , 1999, The Journal of the Acoustical Society of America.

[16]  D. Pisoni,et al.  Speech perception without traditional speech cues. , 1981, Science.

[17]  S. Soli,et al.  Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. , 1994, The Journal of the Acoustical Society of America.

[18]  René H. Gifford,et al.  Speech Recognition Materials and Ceiling Effects: Considerations for Cochlear Implant Programs , 2008, Audiology and Neurotology.

[19]  Robert P Carlyon,et al.  Swinging at a Cocktail Party , 2013, Psychological science.

[20]  Jaimie L. Gilbert,et al.  Development, reliability, and validity of PRESTO: a new high-variability sentence recognition test. , 2013, Journal of the American Academy of Audiology.

[21]  Dennis H. Klatt,et al.  Speech perception: a model of acoustic–phonetic analysis and lexical access , 1979 .

[22]  Matthew H. Davis,et al.  Speech recognition in adverse conditions: A review , 2012 .

[23]  H. Roediger.  Relativity of remembering: why the laws of memory vanished. , 2008, Annual review of psychology.

[24]  Jerker Rönnberg,et al.  Cognitive processing load during listening is reduced more by decreasing voice similarity than by increasing spatial separation between target and masker speech , 2014, Front. Neurosci..

[25]  Terrin N Tamati,et al.  Some factors underlying individual differences in speech recognition on PRESTO: a first report. , 2013, Journal of the American Academy of Audiology.

[26]  W. Luxford,et al.  Minimum Speech Test Battery for Postlingually Deafened Adult Cochlear Implant Patients , 2001, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[27]  R. M. Warren,et al.  Spectral redundancy: Intelligibility of sentences heard through narrow spectral slits , 1995, Perception & psychophysics.

[28]  D. Dirks,et al.  Effects of lexical factors on word recognition among normal-hearing and hearing-impaired listeners. , 2001, Journal of the American Academy of Audiology.

[29]  S. S. Stevens,et al.  The development of recorded auditory tests for measuring hearing loss for speech , 1947, The Laryngoscope.

[30]  Roger K. Moore.  Spoken language processing: Piecing together the puzzle , 2007, Speech Commun..

[31]  H. Nusbaum.  Talker Normalization: Phonetic Constancy as a Cognitive Process , 2011 .

[32]  Bell Ts,et al.  Sentence recognition materials based on frequency of word use and lexical confusability. , 2001 .

[33]  A. Thornton,et al.  Confidence levels for differences between speech-discrimination scores. A research note. , 1980, Journal of speech and hearing research.

[34]  Informational Masking in Profile Analysis: Comparing Ideal and Human Observers , 2001, Journal of the Association for Research in Otolaryngology.

[35]  Mitchell S. Sommers,et al.  The structural organization of the mental lexicon and its contribution to age-related declines in spoken-word recognition. , 1996 .

[36]  David B. Pisoni,et al.  Lexical Effects on Spoken Word Recognition by Pediatric Cochlear Implant Users , 1995, Ear and hearing.

[37]  D. Pisoni,et al.  Speech Perception as a Talker-Contingent Process , 1993, Psychological science.

[38]  Jeremy Goslin,et al.  Does a regional accent perturb speech processing? , 2006, Journal of experimental psychology. Human perception and performance.

[39]  Fergus I. M. Craik,et al.  Four Points to Remember: A Tetrahedral Model of Memory Experiments , 2014 .

[40]  J. P. Egan.  Articulation testing methods , 1948, The Laryngoscope.

[41]  Philipos C. Loizou,et al.  Acoustic Simulations of Combined Electric and Acoustic Hearing (EAS) , 2005, Ear and hearing.

[42]  D B Pisoni,et al.  Stimulus variability and spoken word recognition. I. Effects of variability in speaking rate and overall amplitude. , 1994, The Journal of the Acoustical Society of America.

[43]  Roger K. Moore.  PRESENCE: A Human-Inspired Architecture for Speech-Based Human-Machine Interaction , 2007, IEEE Transactions on Computers.

[44]  H. Nusbaum.  Sizing up the Hoosier Mental Lexicon: Measuring the Familiarity of 20,000 Words, Research on Speech Perception , 1984 .

[45]  Michael F Dorman,et al.  Development and Validation of the Pediatric AzBio Sentence Lists , 2014, Ear and hearing.

[46]  S. T. Goverts,et al.  Measuring the effects of reverberation and noise on sentence intelligibility for hearing-impaired listeners. , 2010, Journal of speech, language, and hearing research : JSLHR.

[47]  K. Kirk,et al.  Assessing multimodal spoken word-in-sentence recognition in children with normal hearing and children with cochlear implants. , 2011, Journal of speech, language, and hearing research : JSLHR.

[48]  J. Mullennix,et al.  Some effects of talker variability on spoken word recognition. , 1989, The Journal of the Acoustical Society of America.

[49]  F. Wightman,et al.  Individual differences and age effects in a dichotic informational masking paradigm. , 2010, The Journal of the Acoustical Society of America.

[50]  B. French,et al.  Lexical Effects on Spoken-Word Recognition in Children with Normal Hearing , 2010, Ear and hearing.

[51]  M. Strube,et al.  Evaluation of TIMIT sentence list equivalency with adult cochlear implant recipients. , 2012, Journal of the American Academy of Audiology.

[52]  J Bamford,et al.  The BKB (Bamford-Kowal-Bench) sentence lists for partially-hearing children. , 1979, British journal of audiology.

[53]  H. Nusbaum,et al.  Neural Bases of Talker Normalization , 2004, Journal of Cognitive Neuroscience.

[54]  R V Shannon,et al.  Speech Recognition with Primarily Temporal Cues , 1995, Science.

[55]  L. Rosenblum,et al.  Lip-Read Me Now, Hear Me Better Later , 2006, Psychological science.

[56]  Qian-Jie Fu,et al.  Noise Susceptibility of Cochlear Implant Users: The Role of Spectral Resolution and Smearing , 2005, Journal of the Association for Research in Otolaryngology.

[57]  W. M. Rabinowitz,et al.  Standardization of a test of speech perception in noise. , 1979, Journal of speech and hearing research.

[58]  H. Nusbaum,et al.  Acoustic differences, listener expectations, and the perceptual accommodation of talker variability. , 2007, Journal of experimental psychology. Human perception and performance.

[59]  M. Killion,et al.  Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners. , 2004, The Journal of the Acoustical Society of America.

[60]  Constance M. Clarke,et al.  Rapid adaptation to foreign-accented English. , 2004, The Journal of the Acoustical Society of America.