doc: fix readme numbering

README.md

@@ -2,10 +2,10 @@
 
 A simple Python package to prepare acoustic data for the Bridge2AI voice project.
 
-**Caution:** this package is still under development and may change rapidly over the next few weeks.
+**Caution:** this package is under activedevelopment and interfaces may change rapidly over the next few weeks.
 
 ## Installation
-Requires a Python >= 3.10 environment
+Requires a Python >= 3.10, <3.12 environment
 
 ```
 pip install b2aiprep
@@ -20,69 +20,68 @@ b2aiprep-cli --help
 
 1. Convert an audio file to features:
 
-The simplest form takes an audio file, a subject id, and a task name.
+    The simplest form takes an audio file, a subject id, and a task name.
 
-```bash
-b2aiprep-cli convert test_audio.wav s1 mpt
-```
+    ```bash
+    b2aiprep-cli convert test_audio.wav s1 mpt
+    ```
 
-It will save a pytorch `.pt` file with a dictionary of features. This can be
-loaded by `torch.load()`. The file is named following a simple convention:
-`sub-<subject_id>_task-<task_name>_md5-<checksum>_features.pt`
+    It will save a pytorch `.pt` file with a dictionary of features. This can be
+    loaded by `torch.load()`. The file is named following a simple convention:
+    `sub-<subject_id>_task-<task_name>_md5-<checksum>_features.pt`
 
-1. Batch process audio files
+2. Batch process audio files
 
-This requires a CSV file, where each line is of the form:
-path/to/audio.wav
+    This requires a CSV file, where each line is of the form:
+    path/to/audio.wav
 
-This also supports a CSV file where each line is of the form:
-path/to/audio.wav,subject_id,task_name
+    This also supports a CSV file where each line is of the form:
+    path/to/audio.wav,subject_id,task_name
 
-To generate this csv file from the Production directory pulled from wasabi, use command 3.
+    To generate this csv file from the Production directory pulled from wasabi, use command 3.
 
-```bash
-b2aiprep-cli batchconvert filelist.csv --plugin cf n_procs=2 --outdir out --save_figures
-```
+    ```bash
+    b2aiprep-cli batchconvert filelist.csv --plugin cf n_procs=2 --outdir out --save_figures
+    ```
 
-The above command uses pydra under the hood to parallel process the audio files.
-All outputs are currently stored in a single directory specified by the `--outdir`
-flag.
+    The above command uses pydra under the hood to parallel process the audio files.
+    All outputs are currently stored in a single directory specified by the `--outdir`
+    flag.
 
-1. Generate csv file to feed to batchconvert
+3. Generate csv file to feed to batchconvert
 
-```bash
-b2aiprep-cli createbatchcsv input_dir outfile
-```
+    ```bash
+    b2aiprep-cli createbatchcsv input_dir outfile
+    ```
 
-The input directory should point to the location of the Production directory pulled from Wasabi e.g. `/Users/b2ai/production`. Don't uninclude a / at the end of your path e.g. `/Users/b2ai/production/` will throw an
-error. This will be fixed later.
+    The input directory should point to the location of the Production directory pulled from Wasabi e.g. `/Users/b2ai/production`. Don't uninclude a / at the end of your path e.g. `/Users/b2ai/production/` will throw an
+    error. This will be fixed later.
 
-This directory is expected to have subfolders for each institution, (e.g. `production/MIT`),
-and each subdirectory is expected to have all the .wav files from each institution
+    This directory is expected to have subfolders for each institution, (e.g. `production/MIT`),
+    and each subdirectory is expected to have all the .wav files from each institution
 
-Outfile is the path to and name of the csv file to be generated, e.g. `audiofiles.csv`
+    Outfile is the path to and name of the csv file to be generated, e.g. `audiofiles.csv`
 
-1. Verify if two audio files are from the same speaker
+4. Verify if two audio files are from the same speaker
 
-```bash
-b2aiprep-cli test_audio1.wav test_audio2.wav --model 'speechbrain/spkrec-ecapa-voxceleb'
-```
-
-This will use the speechbrain speaker recognition model to verify that the two
-audio files are from the same speaker.
+    ```bash
+    b2aiprep-cli test_audio1.wav test_audio2.wav --model 'speechbrain/spkrec-ecapa-voxceleb'
+    ```
 
-There is a notebook in the docs directory that can be used to interact with the library
-programmatically.
+    This will use the speechbrain speaker recognition model to verify that the two
+    audio files are from the same speaker.
 
+    There is a notebook in the docs directory that can be used to interact with the library
+    programmatically.
 
-1. Convert the speaker in the source audio file (1st argument) into the speaker of the target audio file (2nd argument) and save the result in the output file (3rd argument)
+5. Convert the speaker in the source audio file (1st argument) into the speaker of the target audio file (2nd argument) and save the result in the output file (3rd argument)
 
-```bash
-b2aiprep-cli convert-voice data/vc_source.wav data/vc_target.wav data/vc_output.wav
-```
+    ```bash
+    b2aiprep-cli convert-voice data/vc_source.wav data/vc_target.wav data/vc_output.wav
+    ```
 
-1. Transcribe the audio
+6. Transcribe the audio
 
-```bash
-b2aiprep-cli transcribe data/vc_source.wav
-```
+    ```bash
+    b2aiprep-cli transcribe data/vc_source.wav
+    ```