Moved much of this to Drafts instead
phonbank: poor articulation
disfluent kids
late talkers
Write a review about ASR benchmark methods
- REV would be our benchmark
- What corpora we use?
- Has anyone used disordered speech?
- Or really seriously accented speech vis a vi CORALL (how was CORALL sampled?)
- What samples? How do we sample? What are the benchmarks?
- REV would be our benchmark
ASR model + WER
tildes and noprompt swapped
WER
missing words
correct alignment
things
- swap noprompt backwards
- apostrophies for quotes
- the word separation error
- put tilde BETWEEN specific symbols with connection symbols
- jemoka becomes batchalign 2
- Extended UD?
combining
- bash script to run batchalign multiple times throughout the directories
Removing
- removing non-auditory SBCA corpus area
Diarization
- Diarization as a Bi-product of ASR
humans at the end
- do speaker ID in the end
- DO TO BATCHALIGN
- allow people to reject files
runhouse meeting
- <>Donny Greenberg: ADNE, nurses’ health
- implementation at Google: grantees of canniniminty
Remaining questions
- but we can’t provide SSH
- function.save()
- remote
- running through hashicorp vault?
- serializing ssh key remote?
- RUNHOUSE call into remote!
- headscale
- take wave2vec and hubert and GSLM
questions?
- ask about inter-turn pauses, where
- INV: something something something <-
- PAR: WWW <-
- INV: somethingsomething else <-
- PAR: words words word
- no bullets are given for PAR, so do we skip it? do we count the time for WWW all as an inter-turn pause between INV and PAR? etc.
Per Turn
- Turn level analysis
- Rename tier to
Silence duration?
does it include inter-utterance pauses?
within-utterance pause
- fluency, mechanistic
between-utterance pause
- pause between utterances
also: between-speaker pause!
- leaves room for the speaker to take the floor
- BETWEEN speaker pauses: “I don’t know what you are asking me”, etc.: “breakdown!”
add features: STOPPA, TRESTLE, Wang
featurize
- saturnino
- fausa
Questions
- What features?
- Where to put them?
- TalkBankDB
- How to encode the features?
“How informative are your features”
- Start coming up with features (TRESTLE, perhaps)
- Encode them into xarray
- <> saturnino
stuff
- make Spanish names list
- name, city, countries
corpuses
- SABSAE: santa barbara english
- CABNC: British english
next
- ignore any words that goes wrong in the pipeline
~change: noun => n; verb => v, etc.~
- DET: ignore “DEF”, or perhaps the entir featureless
- unbulleted VAD exprimentents
errors!
line 1492
*PAR: so ‡ anyway I tiptoe to the front door , open the front door and walk in . •1045194_1050644• %mor: co|so beg|beg adv|anyway pro:sub|I v|+n|tip+n|toe prep|to det:art|the n|front n|door cm|cm adj|open det:art|the n|front n|door coord|and n|walk adv|in . %gra: 1|0|BEG 2|1|BEGP 3|5|JCT 4|5|SUBJ 5|0|ROOT 6|5|JCT 7|9|DET 8|9|MOD 9|6|POBJ 10|5|LP 11|14|MOD 12|14|DET 13|14|MOD 14|5|OBJ 15|14|CONJ 16|15|COORD 17|16|NJCT 18|5|PUNCT
errors?
- words without features needs to be correctly handled (done in the middle of meeting)
- 04111 (me ma SOS)
- nouns shouldn’t mark if it is Com,Neut, should’nt mark if its Com
- fix PASTP => PAST
- and does past participles exist?
more
- Move shua to d(e)
- Include instructions on how to recreate a broken Conda environment
- Update the package to conda somehow
move
next steps
- deal with `n`
- +… fix
- remove bullets
results
- ~ contraction
- & fused
- suffix
- getting rid of punkt in mor
- , => cm
- . => no PUNKT, stays
stuff
- chocolaty (noadmin, https://docs.chocolatey.org/en-us/choco/setup#non-administrative-install)
- miniconda
- setx path “%path%;C:\tools\miniconda3\condabin”
- curl env first, the install (Windows can’t do it from a URL)
readme
conda init zsh (close shell, open again)- .mp4
- mfa model downloading
- what’s the difference between online docker install and manual install
- NLTK Huggingface transformers tokenizers (versining)
- /opt/homebrew/Caskroom/miniforge/base/envs/aligner/lib/python3.9/site-packages/montreal_forced_aligner/corpus/text_corpus.py; getattr(self, k).update(error_dict[k])
AttributeError: ’list’ object has no attribute ‘update’ FileArgumentNotFoundError: ; line 139
DBA
- See the data on the frequency of haphax legomina vs. COCA
ESPNet
- need to talk to Ji Yang
Andrew’s Features
- Collapse two PAR tiers down
Checkpoint per fileOne corpus prompt per runHandle empty tiersI/P selection crashes! contingencypreview the LONGEST segment instead of the top one-i kill in the middle
fixes
- “my mom’s cryin(g)” [<] mm [l648] (also themmm after)
- “made her a nice dress” [<] mhm [l1086]
- “when I was a kid I” &=laughs [l1278]
Others
chstring (for uh, mm-hmm)
retrace (asr&fa folder)
lowcase (caps)
rep-join.cut (fixes/)
- numbers
- <affirmative>
- ‘mo data!
- CallFriend/CallHome (ca-data)
- ISL?
- SBCSAE
- Aphasia + MICASE
- TBI data
- Providing a Two-Pass Solution
- Writing
- Big description of the pipeline
- Notion of the pipeline
- Better tokenization?
- 8/18
- Initial segment repetition
- Extracting studdering
- Gramatically problematic
mar
- mar has done a thing and its phoneme level
- We did it, now automated
- LEAP data
next actions
- Aphasia (-apraxia?): classification
- Child data (EllisWeismer)
- Dementia
a
~Multiple @Begin/CHECK problem~
~Placement of @Options~
~Strange, missing period~
~Bracket comments should FOLLOW words instead of PRECEEDING them~
~%xwor: line~
STICK TO DASHES WHEN DISTRIBUTING BATCHALIGN
end the utterance when it ends (incl. inter-utterance pauses)
“I” need to be capitalized
11005 (LT)
Align EllisWeismer
Also cool to align:
Alzheimer’s Project
Specifically: https://dementia.talkbank.org/access/English/Pitt.html
Review Kathleen Fraser: https://drive.google.com/drive/u/1/folders/1lYTIzzXLXw3LlDG9ZQ7k4RayDiP6eLs1
Here are the review papers: https://drive.google.com/drive/u/1/folders/1pokU75aKt6vNdeSMpc-HfN9fkLvRyutt
Read this first: https://drive.google.com/drive/u/1/folders/0B3XZtiQwQW4XMnlFN0ZGUndUamM?resourcekey=0-AlOCZb4q9TyG4KpaMQpeoA
Some PITT data have 3-4 recordings
The best way to diagnosing alzhimers’ is from language.
Why this field is needed: to analyze a pre-post test metric.
Desired output: existence of dementia (a.k.a alzheimer’s’).
Other research to read:
- Penn (julia parish something but they don’t stare their data but they smile and things with Mark Libermann type of thing)
- Learning more about speech text
- https://my.clevelandclinic.org/health/diagnostics/22327-differential-diagnosis
python3 ~/mfa_data/batchalign-dist/batchalign.py ~/mfa_data/my_corpus ~/mfa_data/my_corpus_aligned
christan marr paper on MFA on child data