[BUG] (maybe) : mfa acoustic models crash on alignmentError (Russian, Spanish)

[maxime-fily]

Hi,
I'm not 100% sure that this is a bug, but I am getting issues on super small and super simple corpora for russian :

Debugging checklist

[ ] Have you read the troubleshooting page (https://montreal-forced-aligner.readthedocs.io/en/latest/user_guide/troubleshooting.html) and searched the documentation to ensure that your issue is not addressed there? Yes
[ ] Have you updated to latest MFA version (check https://montreal-forced-aligner.readthedocs.io/en/latest/changelog/changelog_3.0.html)? What is the output of mfa version? 3.0.6
[ ] Have you tried rerunning the command with the --clean flag? yes

Describe the issue
A clear and concise description of what the bug is.
when I use russian_mfa dict and acoustic model, I systematically get an "alignmentError", after the validate step worked.
The alignment works functionnally with russian_cv but it is my understanding that if I get to have russain_mfa to work I will get much better alignment performance. Which is why I'd like to insist abit on getting russian_mfa to work.

For Reproducing your issue
Please fill out the following:

1. Corpus structure
   • What language is the corpus in? Russian
   • How many files/speakers? 2/2
   • Are you using lab files or TextGrid files for input? lab
2. Dictionary
   • Are you using a dictionary from MFA? If so, which one? russian_mfa
   • If it's a custom dictionary, what is the phoneset?
3. Acoustic model
   • If you're using an acoustic model, is it one download through MFA? If so, which one? russian_mfa
   • If it's a model you've trained, what data was it trained on?

Log file

Please attach the log file for the run that encountered an error (by default these will be stored in ~/Documents/MFA).

2024-04-23 16:06:59,330 - mfa - DEBUG - Beginning run for test_RU
2024-04-23 16:06:59,330 - mfa - DEBUG - Using "global" profile
2024-04-23 16:06:59,330 - mfa - DEBUG - Using multiprocessing with 3
2024-04-23 16:06:59,330 - mfa - DEBUG - Set up logger for MFA version: 3.0.6
2024-04-23 16:06:59,522 - mfa - INFO - Setting up corpus information...
2024-04-23 16:06:59,524 - mfa - DEBUG - Successfully loaded from temporary files
2024-04-23 16:06:59,529 - mfa - INFO - Found 2 speakers across 2 files, average number of utterances per speaker: 1.0
2024-04-23 16:06:59,530 - mfa - DEBUG - Loaded corpus in 0.008 seconds
2024-04-23 16:06:59,531 - mfa - INFO - Jobs already initialized.
2024-04-23 16:06:59,532 - mfa - DEBUG - Initialized jobs in 0.002 seconds
2024-04-23 16:06:59,532 - mfa - INFO - Text already normalized.
2024-04-23 16:07:01,164 - mfa - INFO - Features already generated.
2024-04-23 16:07:01,164 - mfa - DEBUG - Generated features in 0.001 seconds
2024-04-23 16:07:01,164 - mfa - DEBUG - Setting up corpus took 1.643 seconds
2024-04-23 16:07:01,164 - mfa - DEBUG -
2024-04-23 16:07:01,164 - mfa - DEBUG - ====ACOUSTIC MODEL INFO====
2024-04-23 16:07:01,164 - mfa - DEBUG - Acoustic model root directory: /home/mfily/Documents/MFA/extracted_models/acoustic
2024-04-23 16:07:01,164 - mfa - DEBUG - Acoustic model dirname: /home/mfily/Documents/MFA/extracted_models/acoustic/russian_mfa_acoustic
2024-04-23 16:07:01,164 - mfa - DEBUG - Acoustic model meta path: /home/mfily/Documents/MFA/extracted_models/acoustic/russian_mfa_acoustic/meta.json
2024-04-23 16:07:01,164 - mfa - DEBUG - Acoustic model meta information:
2024-04-23 16:07:01,167 - mfa - DEBUG - architecture: gmm-hmm
dictionaries:
bracketed_word: '[bracketed]'
clitic_marker: ''''
default: russian_mfa
laughter_word: '[laughter]'
names:

• russian_mfa
  oov_word:
  position_dependent_phones: true
  silence_word:
  use_g2p: false
  features:
  allow_downsample: true
  allow_upsample: true
  delta_pitch: 0.005
  feature_type: mfcc
  frame_length: 25
  frame_shift: 10
  high_frequency: 7800
  low_frequency: 20
  max_f0: 500
  min_f0: 50
  penalty_factor: 0.1
  sample_frequency: 16000
  snip_edges: true
  use_delta_pitch: true
  use_energy: false
  use_pitch: true
  use_voicing: true
  uses_cmvn: true
  uses_deltas: false
  uses_speaker_adaptation: true
  uses_splices: true
  uses_voiced: false
  final_non_silence_correction: 0.1
  final_silence_correction: 2.06
  initial_silence_probability: 0.21
  language: unknown
  oov_phone: spn
  optional_silence_phone: sil
  phone_set_type: IPA
  phone_type: triphone
  phones: !!set
  a: null
  b: null
  "b\u02B2": null
  "b\u02B2\u02D0": null
  "b\u02D0": null
  c: null
  "c\u02D0": null
  "dz\u02B2": null
  "dz\u02B2\u02D0": null
  "d\u0290": null
  "d\u0290\u02D0": null
  "d\u02B2": null
  "d\u02B2\u02D0": null
  "d\u032A": null
  "d\u032Az\u032A": null
  "d\u032Az\u032A\u02D0": null
  "d\u032A\u02D0": null
  e: null
  f: null
  "f\u02B2": null
  "f\u02B2\u02D0": null
  "f\u02D0": null
  i: null
  j: null
  "j\u02D0": null
  k: null
  "k\u02D0": null
  m: null
  "m\u02B2": null
  "m\u02B2\u02D0": null
  "m\u02D0": null
  "n\u032A": null
  "n\u032A\u02D0": null
  o: null
  p: null
  "p\u02B2": null
  "p\u02B2\u02D0": null
  "p\u02D0": null
  r: null
  "r\u02B2": null
  "r\u02B2\u02D0": null
  "r\u02D0": null
  "s\u02B2": null
  "s\u02B2\u02D0": null
  "s\u032A": null
  "s\u032A\u02D0": null
  "ts\u02B2": null
  "t\u0255": null
  "t\u0255\u02D0": null
  "t\u0282": null
  "t\u0282\u02D0": null
  "t\u02B2": null
  "t\u02B2\u02D0": null
  "t\u032A": null
  "t\u032As\u032A": null
  "t\u032As\u032A\u02D0": null
  "t\u032A\u02D0": null
  u: null
  v: null
  "v\u02B2": null
  "v\u02B2\u02D0": null
  "v\u02D0": null
  x: null
  "x\u02D0": null
  "z\u02B2": null
  "z\u02B2\u02D0": null
  "z\u032A": null
  "z\u032A\u02D0": null
  "\xE6": null
  "\xE7": null
  "\u0250": null
  "\u0255": null
  "\u0255\u02D0": null
  "\u0259": null
  "\u025B": null
  "\u025F": null
  "\u025F\u02D0": null
  "\u0261": null
  "\u0261\u02D0": null
  "\u0263": null
  "\u0268": null
  "\u026A": null
  "\u026B": null
  "\u026B\u02D0": null
  "\u0272": null
  "\u0272\u02D0": null
  "\u0275": null
  "\u0282": null
  "\u0282\u02D0": null
  "\u0289": null
  "\u028A": null
  "\u028E": null
  "\u028E\u02D0": null
  "\u0290": null
  "\u0290\u02D0": null
  "\u0291": null
  "\u0291\u02D0": null
  silence_probability: 0.21470002836195884
  train_date: '2022-05-20 00:19:00.209288'
  training:
  audio_duration: 1385812.0378750225
  average_log_likelihood: -0.01083423597600454
  num_oovs: 0
  num_speakers: 2355
  num_utterances: 232271
  version: 2.0.0rc4.dev19+ged818cb.d20220404

2024-04-23 16:07:01,167 - mfa - DEBUG -
2024-04-23 16:07:01,167 - mfa - DEBUG - Setup for alignment in 1.785 seconds
2024-04-23 16:07:01,317 - mfa - INFO - Compiling training graphs...
2024-04-23 16:07:04,363 - mfa - DEBUG - Compiling training graphs took 3.046 seconds
2024-04-23 16:07:04,364 - mfa - INFO - Performing first-pass alignment...
2024-04-23 16:07:04,367 - mfa - INFO - Generating alignments...
2024-04-23 16:07:05,644 - mfa - ERROR - There was an error in the run, please see the log.

Desktop (please complete the following information):

• OS: [e.g. Windows, OSX, Linux] : Linux
• Version [e.g. MacOSX 10.15, Ubuntu 20.04, Windows 10, etc] Ubuntu 22.04
• Any other details about the setup (Cloud, Docker, etc)
  Same issue whether I run directly on a terminal or via docker
  Additional context
  Add any other context about the problem here.
  The issue is similar for Spanish, which is all the more surprising. But maybe it is that these acoustic models are less robust than French and English... Indeed, these two work OK.

[maxime-fily]

Hi. I finally ended up retraining the acoustic module on the CV dataset for Russian. It works much better now. Should I post the retrained acoustic model somewhere ?