[AUDITORY] Fwd: Tool for automatic syllable segmentation (Jonathan James Digby )

Subject: [AUDITORY] Fwd: Tool for automatic syllable segmentation From: Jonathan James Digby <digbyphonic@xxxxxxxx> Date: Tue, 24 Sep 2024 08:59:40 +0100 This is a multipart message in MIME format. ------=_NextPart_000_008D_01DB0E60.175690C0 Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: quoted-printable Thank you very much for sharing your article, Oded. May be off-topic, but could be of interest to the discussion: =20 Bloom, Jon, =E2=80=98A Standard for Morse Timing Using the Farnsworth = Technique=E2=80=99 (1990) = <https://www.arrl.org/files/file/Technology/x9004008.pdf> [accessed 24 = September 2024] =20 Have a good day, all. _________________________________ Jonathan J Digby =20 =20 Sent: 22 September 2024 15:11 Humbly, here is my take on Alain's cautionary note: = <https://doi.org/10.3389/fpsyg.2013.00138> = https://doi.org/10.3389/fpsyg.2013.00138 -- Oded. =20 =20 On Sun, Sep 22, 2024 at 12:08=E2=80=AFAM Alain de Cheveigne = <alain.de.cheveigne@xxxxxxxx <mailto:alain.de.cheveigne@xxxxxxxx> > = wrote: Curiously, no one yet pointed out that "segmentation" itself is = ill-defined. Syllables, like phonemes, are defined at the phonological = level which is abstract and distinct from the acoustics. =20 Acoustic cues to a phoneme (or syllable) may come from an extended = interval of sound that overlaps with the cues that signal the next = phoneme. I seem to recall papers by Hynek Hermansky that found a support = duration on the order of 1s. If so, the "segmentation boundary" between = phonemes/syllables is necessarily ill-defined.=20 In practice, it may be possible to define a segmentation that = "concentrates" information pertinent to each phoneme within a segment = and minimizes "spillover" to adjacent phonemes, but we should not be = surprised if it works less well for some boundaries, or if different = methods give different results. When listening to Japanese practice tapes, I remember noticing that the = word "futatsu" (two) sounded rather like "uftatsu", suggesting that the = acoustic-to-phonological mapping (based on my native phonological = system) could be loose enough to allow for a swap.=20 Alain=20 > On 20 Sep 2024, at 11:29, Jan Schnupp = <000000e042a1ec30-dmarc-request@xxxxxxxx = <mailto:000000e042a1ec30-dmarc-request@xxxxxxxx> > wrote: >=20 > Dear Remy, >=20 > it might be useful for us to know where your meaningless CV syllable = stimuli come from.=20 > But in any event, if you are any good at coding you are likely better = off working directly computing parameters of the recording waveforms and = apply criteria to those. CV syllables have an "energy arc" such that the = V is invariably louder than the C. In speech there are rarely silent = gaps between syllables, so you may be looking at a CVCVCVCV... stream = where the only "easy" handle on the syllable boundary is likely to be = the end of end of the vowel, which should be recognizable by a marked = decline in acoustic energy, which you can quantify by some running RMS = value (perhaps after low-pass filtering given that consonants rarely = have much low frequency energy). If that's not accurate or reliable = enough then things are likely to get a lot trickier. You could look for = voicing in a running autocorrelation as an additional cue given that all = vowels are voiced but only some consonants are.=20 > How many of these do you have to process? If the number isn't huge, it = may be quicker to find the boundaries "by ear" than trying to develop a = piece of computer code. The best way forward really depends enormously = on the nature of your original stimulus set.=20 >=20 > Best wishes, >=20 > Jan >=20 > --------------------------------------- > Prof Jan Schnupp > Gerald Choa Neuroscience Institute > The Chinese University of Hong Kong > Sha Tin > Hong Kong >=20 > https://auditoryneuroscience.com > http://jan.schnupp.net >=20 >=20 > On Thu, 19 Sept 2024 at 12:19, R=C3=A9my MASSON = <remy.masson@xxxxxxxx <mailto:remy.masson@xxxxxxxx> > wrote: > Hello AUDITORY list, > We are attempting to do automatic syllable segmentation on a = collection of sound files that we use in an experiment. Our stimuli are = a rapid sequence of syllables (all beginning with a consonant and ending = with a vowel) with no underlying semantic meaning and with no pauses. We = would like to automatically extract the syllable/speech rate and obtain = the timestamps for each syllable onset. > We are a bit lost on which tool to use. We tried PRAAT with the = Syllable Nuclei v3 script, the software VoiceLab and the website = WebMaus. Unfortunately, for each of them their estimation of the total = number of syllables did not consistently match what we were able to = count manually, despite toggling with the parameters. =20 > Do you have any advice on how to go further? Do you have any = experience in syllable onset extraction? > Thank you for your understanding, > R=C3=A9my MASSON > Research Engineer > Laboratory "Neural coding and neuroengineering of human speech = functions" (NeuroSpeech) > Institut de l=E2=80=99Audition =E2=80=93 Institut Pasteur (Paris)<imag =20 ------=_NextPart_000_008D_01DB0E60.175690C0 Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: quoted-printable <html xmlns:v=3D"urn:schemas-microsoft-com:vml" = xmlns:o=3D"urn:schemas-microsoft-com:office:office" = xmlns:w=3D"urn:schemas-microsoft-com:office:word" = xmlns:m=3D"http://schemas.microsoft.com/office/2004/12/omml" = xmlns=3D"http://www.w3.org/TR/REC-html40"><head><meta = http-equiv=3DContent-Type content=3D"text/html; charset=3Dutf-8"><meta = name=3DGenerator content=3D"Microsoft Word 15 (filtered = medium)"><style></style></head><body lang=3DEN-CA = link=3D"#467886" vlink=3D"#96607D" style=3D'word-wrap:break-word'><div = class=3DWordSection1>Thank you very much for = sharing your article, Oded.<o:p></o:p>May be off-topic, but could be of interest to the = discussion:<o:p></o:p><o:p> </o:p>Bloom, Jon, =E2=80=98A = Standard for Morse Timing Using the Farnsworth Technique=E2=80=99 (1990) = <<a = href=3D"https://www.arrl.org/files/file/Technology/x9004008.pdf">https://= www.arrl.org/files/file/Technology/x9004008.pdf</a>> [accessed 24 = September 2024]<o:p></o:p><o:p> </o:p>Have a good day, = all.<o:p></o:p>____________________________= _____<o:p></o:p></= p>Jonathan J = Digby<o:p></o:p></= p><o:p> </o:p><o:p> </o:p> Sent:<= /b> 22 September 2024 15:11 <o:p></o:p>Humbly, here is my take on Alain's cautionary note: <a = href=3D"https://doi.org/10.3389/fpsyg.2013.00138" = target=3D"_blank">https://doi.org/10.3389/fpsyg.2013.00138</a> <o:p></o:p>--<o:p></o:p>Oded.<o:p></o:p><o:p> </o:p><o:p> </o:p>On Sun, Sep = 22, 2024 at 12:08=E2=80=AFAM Alain de = Cheveigne <<a href=3D"mailto:alain.de.cheveigne@xxxxxxxx" = target=3D"_blank">alain.de.cheveigne@xxxxxxxx</a>> = wrote:<o:p></o:p>Curiously, no one yet pointed = out that "segmentation" itself is ill-defined.  = Syllables, like phonemes, are defined at the phonological level which is = abstract and distinct from the acoustics.  Acoustic cues to = a phoneme (or syllable) may come from an extended interval of sound that = overlaps with the cues that signal the next phoneme. I seem to recall = papers by Hynek Hermansky that found a support duration on the order of = 1s. If so, the "segmentation boundary" between = phonemes/syllables is necessarily ill-defined. In practice, it = may be possible to define a segmentation that "concentrates" = information pertinent to each phoneme within a segment and minimizes = "spillover" to adjacent phonemes, but we should not be = surprised if it works less well for some boundaries, or if different = methods give different results. When listening to Japanese = practice tapes, I remember noticing that the word "futatsu" = (two) sounded rather like "uftatsu", suggesting that the = acoustic-to-phonological mapping (based on my native phonological = system) could be loose enough to allow for a swap. Alain = > On 20 Sep 2024, at 11:29, Jan Schnupp <<a = href=3D"mailto:000000e042a1ec30-dmarc-request@xxxxxxxx" = target=3D"_blank">000000e042a1ec30-dmarc-request@xxxxxxxx</a>> = wrote: > > Dear Remy, > > it might be useful = for us to know where your meaningless CV syllable stimuli come from. = > But in any event, if you are any good at coding you are likely = better off working directly computing parameters of the recording = waveforms and apply criteria to those. CV syllables have an "energy = arc" such that the V is invariably louder than the C. In speech = there are rarely silent gaps between syllables, so you may be looking at = a CVCVCVCV... stream where the only "easy" handle on the = syllable boundary is likely to be the end of end of the vowel, which = should be recognizable by a marked decline in acoustic energy, which you = can quantify by some running RMS value (perhaps after low-pass filtering = given that consonants rarely have much low frequency energy). If that's = not accurate or reliable enough then things are likely to get a lot = trickier. You could look for voicing in a running autocorrelation as an = additional cue given that all vowels are voiced but only some consonants = are. > How many of these do you have to process? If the number = isn't huge, it may be quicker to find the boundaries "by ear" = than trying to develop a piece of computer code. The best way forward = really depends enormously on the nature of your original stimulus set. = > > Best wishes, > > Jan > > = --------------------------------------- > Prof Jan Schnupp > = Gerald Choa Neuroscience Institute > The Chinese University of = Hong Kong > Sha Tin > Hong Kong > > <a = href=3D"https://auditoryneuroscience.com" = target=3D"_blank">https://auditoryneuroscience.com</a> > <a = href=3D"http://jan.schnupp.net" = target=3D"_blank">http://jan.schnupp.net</a> > > > = On Thu, 19 Sept 2024 at 12:19, R=C3=A9my MASSON <<a = href=3D"mailto:remy.masson@xxxxxxxx" = target=3D"_blank">remy.masson@xxxxxxxx</a>> wrote: > Hello = AUDITORY list, >  We are attempting to do automatic syllable = segmentation on a collection of sound files that we use in an = experiment. Our stimuli are a rapid sequence of syllables (all beginning = with a consonant and ending with a vowel) with no underlying semantic = meaning and with no pauses. We would like to automatically extract the = syllable/speech rate and obtain the timestamps for each syllable = onset. >  We are a bit lost on which tool to use. We tried = PRAAT with the Syllable Nuclei v3 script, the software VoiceLab and the = website WebMaus. Unfortunately, for each of them their estimation of the = total number of syllables did not consistently match what we were able = to count manually, despite toggling with the parameters.  = >  Do you have any advice on how to go further? Do you have = any experience in syllable onset extraction? >  Thank you for = your understanding, >  R=C3=A9my MASSON > Research = Engineer > Laboratory "Neural coding and neuroengineering of = human speech functions" (NeuroSpeech) > Institut de = l=E2=80=99Audition =E2=80=93 Institut Pasteur (Paris)<imag<o:p></o:p><o:p> </o:p></div></body></html> ------=_NextPart_000_008D_01DB0E60.175690C0--

This message came from the mail archive
postings/2024/
maintained by:

DAn Ellis <dpwe@ee.columbia.edu>
Electrical Engineering Dept., Columbia University