evaluate

Evaluating SeamlessM4T models

Refer to the SeamlessM4T README for an overview of the M4T models.

Refer to the inference README for how to run inference with SeamlessM4T models.

Quick start:

We use SACREBLEU library for computing BLEU scores and JiWER library is used to compute these CER and WER scores.

Evaluation can be run with the CLI, from the root directory of the repository.

The model can be specified with --model_name: seamlessM4T_v2_large or seamlessM4T_large or seamlessM4T_medium

m4t_evaluate --data_file <path_to_data_tsv_file> --task <task_name> --tgt_lang <tgt_lang> --output_path <path_to_save_evaluation_output> --ref_field <ref_field_name> --audio_root_dir <path_to_audio_root_directory>

Note

1. We use raw (unnormalized) references to compute BLEU scores for S2TT, T2TT tasks.
2. For ASR task, src_lang needs to be passed as <tgt_lang>
3. --src_lang arg needs to be specified to run evaluation for T2TT task