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✖ 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: EmoSpoofTTS | |
| description: > | |
| Spoof-only attack corpus of emotional TTS synthesis (Mahapatra et al., | |
| "Can Emotion Fool Anti-spoofing?", Interspeech 2025): 36,000 clips from | |
| 3 TTS systems (StyleTTS2, F5-TTS, CosyVoice) x 10 ESD speakers x 4 emotions. | |
| It contains NO bonafide audio (every label = 1 = spoof), so it is scored with | |
| the 1-SRR metric (srr_complement): the fraction of these emotional-TTS spoofs | |
| 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). EER on this dataset alone is | |
| degenerate and is not used. | |
| 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 | |