Datasets:
YAML Metadata Error:Invalid content in eval.yaml.
Check out the documentation for more information.
Show details
✖ Invalid option: expected one of "prompt_template"|"system_message"|"user_message"|"chain_of_thought"|"use_tools"|"generate"|"self_critique"|"multiple_choice"
→ at tasks[0].solvers[0].name
✖ Invalid option: expected one of "includes"|"match"|"pattern"|"answer"|"exact"|"f1"|"model_graded_qa"|"model_graded_fact"|"choice"
→ at tasks[0].scorers[0].name
| name: LRLspoof | |
| description: > | |
| LRLspoof - a large multilingual low-resource-language anti-spoofing benchmark | |
| of 1,304,455 text-to-speech (spoof) utterances spanning 66 languages and many | |
| TTS systems. It is SPOOF-ONLY (no bonafide), so it is scored with the 1-SRR | |
| metric (srr_complement): the fraction of spoof NOT rejected at a fixed | |
| operating threshold t* transferred from DeepVoice (lower is better). Every | |
| model must carry a DeepVoice submission to derive t* (placed in the | |
| submission's `calibration` block). The 500+ GB audio is NOT stored in this | |
| arena entry - it lives as a multi-part tarball in the source repo; only | |
| data/labels.parquet (utterance_id -> label, every label = 1 = spoof) is | |
| shipped here. utterance_id = the audio file's path relative to the dataset | |
| root, e.g. "english/fastpitch/line_59.wav". | |
| evaluation_framework: inspect-ai | |
| tasks: | |
| - id: antispoofing_eval | |
| config: default | |
| split: test | |
| field_spec: | |
| input: audio | |
| target: label | |
| solvers: | |
| - name: speech_spoof_bench_solver | |
| scorers: | |
| - name: speech_spoof_scorer | |
| metrics: | |
| - srr_complement | |