Subject: Re: sinfa using matlab From: Thomas Ulrich Christiansen <thomas@xxxxxxxx> Date: Mon, 28 Mar 2016 13:39:37 +0200 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>Dear Jont and List, I couldn't resist the kind invitation to discuss the analysis of consonant confusions... I agree with Jont that SINFA may not be the best way to analyse consonant confusions. I also agree that confusion data is quite complex. My interpretation of this is that using only one analysis method will limit our understanding rather than extend it. I disagree that it is time to give up on distinctive features as they *do* provide insights into certain aspects of consonant confusions (e.g. spectral integration as described in Christiansen and Greenberg, 2012). The fact that distinctive features are defined by production characteristics does not, in my view, preclude them from playing a role in perception. This is indeed what the data from Christiansen and Greenberg, 2012 says. Moreover, this data cannot be explained by AI, which is why I argue that we need to be open to different ways of analysis and interpretation (and even open to degrading the speech signal by other means than noise - e.g. band-pass filtering). Now, I do recognize the vast amount of valuable AI work and the attention it has received. All I am saying is that perhaps it is time to *also* pay attention to alternatives. This is my poppyseed-free two cents... Reference: Christiansen, T.U. and Greenberg, S. (2012) Perceptual confusions among consonans, Revisited – Cross-spectral Integration of phonetic-feature information and consonant recognition. IEEE Trans. Audio, Speech and Lang. Proc. 20: 147-161 Best regards, Thomas Ulrich Christiansen, PhD Senior Research and Development Engineer Audiological Requirements Audiology and Embedded Solutions Oticon A/S Kongebakken 9 DK - 2765 Smørum Denmark Direct: +45 3913 7675 Main: : +45 3917 7100 Mail: thch@xxxxxxxx Web: www.oticon.com Jont Allen skrev den 27-03-2016 14:46: > Dear All, > > My comment is not about HOW to get SINFA working, but WHY you would > want to get it working. > > Since 1973 we have learned a great deal about phone identification by > normal and hearing impaired listeners. Bob Bilger was a good friend, > and his work represented > an important stepping stone along the path toward building realistic > and correct understanding of human speech processing. But today, in my > view, SINFA is not a viable > way to analyze human speech errors. One of the problems with the 1973 > analysis was due to the limitations of computers in 1973. All the > responses were averaged over > the two main effects, tokens and SNR. This renders the results > uninterperateable. > > Please share with us your thoughts on what the best methods are today, > given what we now know. And I would be happy to do the same. > > My view: > > I would suggest you look at the alternatives, such as confusion > patterns, which is a row of a confusion matrix, as a function of SNR, > and most importantly, go down to > the token level. It is time to give up on distinctive features. They > are a production concept, great at classifying different types of > speech productions, but they > do not properly get at what human listeners do, especially those with > hearing loss, when reporting individual consonants. Bilger and Wang > make these points in their HSHR article. > They emphasize individual differences of HI listeners (p 737), and the > secondary role of distinctive features (p. 724) and of hearing level > (p 737). I do not think that multidimentional scaling can give the > answers to these questions, as it only works for a limited number of > dimensions (2 or 3). Actual confusion data, as a function of SNR, are > too complex for a 2-3 dimension analysis. > > Here are some pointers I suggest you consider, that describe how > humans decode CV sounds as a function of the SNR. > > The Singh analysis explains why and how the articulation index (AI) > works. > The Trevino article shows the very large differences in consonant > perception in impaired ears. Hearing loss leads to large individual > differences, that are uncorrelated to hearing thresholds. > The Toscano article is a good place to start. > > * Toscano, Joseph and Allen, Jont B (2014) _Across and within > consonant errors for isolated syllables in noise,_ Journal of Speech, > Language, and Hearing Research, Vol 57, pp 2293-2307; > doi:10.1044/2014_JSLHR-H-13-0244, (JSLHR [6],pdf [7], AuthorCopy [8]) > > * Trevino, Andrea C and Allen, Jont B (2012). "Within-Consonant > Perceptual Differences in the Hearing Impaired Ear," JASA v134(1); > Jul, 2013, pp 607--617 (pdf [9]) > > * Riya Singh and Jont Allen (2012); "The influence of stop > consonants’ perceptual features on the Articulation Index model," J. > Acoust. Soc. Am., apr v131,3051-3068 (pdf [10]) > > These two publications describe the speech cues normal hearing > listeners use when decoding CV sounds. Each token has a threshold we > call SNR_90, defined as the SNR where the errors go form zero to 10%. > Most speech sounds are below the Shannon channel capacity limit, below > which there are zero errors, until the SNR is at the token error > threshold. > > Distinctive features are not a good description of phone perception. > The real speech cues are relieved in these papers, and each token has > an SNR_90. Bilger and wang discuss this problem on page 724 of their > 1973 JSHR article. > > * Li, F., Trevino, A., Menon, A. and Allen, Jont B (2012). "A > psychoacoustic method for studying the necessary and sufficient > perceptual cues of American English fricative consonants in noise" J. > Acoust. Soc. Am., v132(4) Oct, pp. 2663-2675 pdf [11] > > * F. Li, A. Menon, and Jont B Allen, (2010) _A psychoacoustic method > to find the perceptual cues of stop consonants in natural speech_, > apr, _J. Acoust. Soc. Am._ pp. 2599-2610, (pdf [12]) > > If you want to see another view, other than mine, read this, for > starters: > > Zaar, Dau, 2015, JASA vol 138, pp 1253-1267 > > http://scitation.aip.org/content/asa/journal/jasa/138/3/10.1121/1.4928142 > [13] > > Jont Allen > > On 03/26/2016 10:44 AM, gvoysey wrote: > >> I have not tried this, but i am willing to bet you can get FIX >> running on a modern PC with DOSbox [4], which is a cross-platform >> MS-DOS emulator. It’s most famous for letting you play very old >> video games in your web browser (http://playdosgamesonline.com/ >> [5]), but there’s no reason it shouldn’t work just as well for >> Real Work. >> >> -graham >> >> >> On Sat, Mar 26, 2016 at 5:06 AM, David Jackson Morris >> <dmorris@xxxxxxxx> wrote: >> >>> Dear Skyler, >>> >>> I have been on a similar search and found an R package by David >>> van Leeuwen that is available at github. Please let me know if >>> you find any other alternatives? >>> >>> FIX is really awesome, but every time I want to use it I have to >>> go over to Grannies and boot the Win 95 machine, and she makes me >>> eat poppyseed cake which makes me tummy sore. . . >>> >>> Cheers >>> >>> DAVID JACKSON MORRIS, PHD >>> >>> KØBENHAVNS UNIVERSITET/UNIVERSITY OF COPENHAGEN >>> >>> INSS/Audiologopædi/Speech Pathology & Audiology >>> Byggning 22, 5 sal >>> >>> Njalsgade 120 >>> >>> 2300 København S >>> >>> Office 22.5.14 >>> >>> TLF 35328660 >>> dmorris@xxxxxxxx >>> >>> University website [1] >>> >>> ------------------------- >>> >>> FROM: AUDITORY - Research in Auditory Perception >>> [AUDITORY@xxxxxxxx on behalf of Skyler Jennings >>> [Skyler.Jennings@xxxxxxxx >>> SENT: Friday, March 25, 2016 9:15 PM >>> TO: AUDITORY@xxxxxxxx >>> SUBJECT: sinfa using matlab >>> >>> Dear list, >>> >>> I am writing in search of MATLAB-based software that performs >>> sequential information transfer (SINFA; Wang and Bilger, 1973). I >>> am impressed with the quality of the DOS-based software maintained >>> by UCL called “FIX;” however, it would be more convenient to >>> do the analysis in MATLAB if possible. >>> >>> I appreciate any help you can offer, whether it be guiding me to >>> publically-available software, or sharing software that you’ve >>> developed. >>> >>> Sincerely, >>> >>> Skyler >>> >>> -- >>> >>> Skyler G. Jennings, Ph.D., Au.D. CCC-A >>> >>> Assistant Professor >>> >>> Department of Communication Sciences and Disorders >>> >>> College of Health University of Utah >>> >>> 390 South 1530 East >>> >>> Suite 1201 BEHS >>> >>> Salt Lake City, UT 84112 >>> >>> 801-581-6877 [2] (phone) >>> >>> 801-581-7955 [3] (fax) >>> >>> skyler.jennings@xxxxxxxx >> >> -- >> >> Graham Voysey >> Boston University College of Engineering >> HRC Research Engineer >> Auditory Biophysics and Simulation Laboratory >> ERB 413 > > > > Links: > ------ > [1] > https://urldefense.proofpoint.com/v2/url?u=http-3A__forskning.ku.dk_find-2Den-2Dforsker_-3Fpure-3Dda-252Fpersons-252Fdavid-2Djackson-2Dmorris-2865eea758-2D6dd2-2D4783-2Dae28-2Deef3d5ef83ce-29.html&d=BQMFaQ&c=8hUWFZcy2Z-Za5rBPlktOQ&r=N7KKV9mcvQqNgAal48W_vzPUNrKl5mBxlJo8xP9z028&m=AQ_tsotHEkEP4CuE50mpAXGNS5ekvVC321rWDo1X6Vs&s=SP20p9UskD0LOFatpHoojsCUumO5ha0JSvXabOQe8uo&e= > [2] tel:801-581-6877 > [3] tel:801-581-7955 > [4] > https://urldefense.proofpoint.com/v2/url?u=http-3A__www.dosbox.com_&d=BQMFaQ&c=8hUWFZcy2Z-Za5rBPlktOQ&r=N7KKV9mcvQqNgAal48W_vzPUNrKl5mBxlJo8xP9z028&m=AQ_tsotHEkEP4CuE50mpAXGNS5ekvVC321rWDo1X6Vs&s=bfDR3yzi298jK3qIXb9EjBuUZV6Ywvl6JFL4K_XWWdk&e= > [5] > https://urldefense.proofpoint.com/v2/url?u=http-3A__playdosgamesonline.com_&d=BQMFaQ&c=8hUWFZcy2Z-Za5rBPlktOQ&r=N7KKV9mcvQqNgAal48W_vzPUNrKl5mBxlJo8xP9z028&m=AQ_tsotHEkEP4CuE50mpAXGNS5ekvVC321rWDo1X6Vs&s=Cqht_GtwPnX_rGl46sGlvPWkwpH3SQzkLvtQAopRX-g&e= > [6] http://jslhr.pubs.asha.org/Article.aspx?articleid=1894924 > [7] http://173.161.115.245/Public/ToscanoAllenJSLHR.14.pdf > [8] http://173.161.115.245/Public/Toscano-Allen-JSLHR-2014.pdf > [9] http://173.161.115.245/Public/TrevinoAllenJul.13.pdf > [10] http://173.161.115.245/Public/SinghAllen12.pdf > [11] http://173.161.115.245/Public/LiTrevinoMenonAllen12.pdf > [12] http://173.161.115.245/Public/LiMenonAllen10.pdf > [13] > http://scitation.aip.org/content/asa/journal/jasa/138/3/10.1121/1.4928142