In practice, you may need eval your custom audio dataset.
before this, you need now how launch a custom eval task: how launch a custom eval task.md
here are steps:
- make sure your dataset file is
jsonl
format and withWavPath
column which specific the audio file path. - new a file
**.yaml
inregistry/dataset/
content like :$name: # name after cli: --dataset $name class: audio_evals.dataset.dataset.JsonlFile args: default_task: alei_asr # you should specify an eval task as default, you can find valid task in `registry/eval_task` f_name: # the file name ref_col: # the reference answer column name in file
after registry dataset, you can eval your dataset with --dataset $name, enjoy 😘
Example:
- create a file
my_dataset.jsonl
withWavPath
andTranscript
columns, the content like this:
{"WavPath": "path/to/audio1.wav", "Transcript": "this is the first audio"}
{"WavPath": "path/to/audio2.wav", "Transcript": "this is the second audio"}
- create a file
my_dataset.yaml
inregistry/dataset/
with content:
my_dataset:
class: audio_evals.dataset.dataset.JsonlFile
args:
default_task: asr
f_name: my_dataset.jsonl # the file name
ref_col: Transcript # the reference answer column name in file
- eval your dataset with
--dataset my_dataset
export PYTHONPATH=$PWD:$PYTHONPATH
export OPENAI_API_KEY=$your-key
python audio_evals/main.py --dataset my_dataset --model gpt4o_audio